4. Insight JS code (with summary)

(() => {
// Minimal utilities
const qs = (sel, root=document) => root.querySelector(sel);
const esc = (s) => String((s === null || s === undefined) ? ” : s)
.replaceAll(‘&’,’&’).replaceAll(‘<','<') .replaceAll('>‘,’>’).replaceAll(‘”‘,’"’)
.replaceAll(“‘”,”'”);

/**
* Allow ONLY basic inline formatting tags that you expect in Formidable content.
* Everything else remains escaped (so no scripts, no arbitrary HTML).
*/
function safeBasicHtml(raw) {
let h = esc(raw);

// allow a small whitelist of tags
h = h.replace(/<(\/?)(strong|em|b|i)>/gi, ‘<$1$2>‘);
h = h.replace(/<br\s*\/?>/gi, ‘
‘);

// preserve newlines as line breaks
h = h.replace(/\r\n|\r|\n/g, ‘
‘);

return h;
}

// Match GTKY behaviour: allow ?lang=en-GB, default en-GB
function getParam(name, fallback = ”) {
const p = new URLSearchParams(window.location.search);
const v = p.get(name);
return String(v == null ? fallback : v).trim();
}
const langVariant = (getParam(‘lang’, ”) || ‘en-GB’).trim() || ‘en-GB’;

// GTKY-equivalent spellcheck, but via your MU proxy (cpVars.insightPage.aiUrl)
async function spellcheckLocale(text) {
try {
const original = String(text || ”).trim();
if (!original) return text;

// Do not spellcheck very short replies like “no”, “yes”, “maybe”, etc.
if (original.length <= 3) return original; const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {}; if (!v.aiUrl) return original; const headers = { 'Content-Type': 'application/json' }; if (v.token) headers['X-CP-Token'] = v.token; else if (v.restNonce) headers['X-WP-Nonce'] = v.restNonce; const payload = { model: 'gpt-4o', temperature: 0, messages: [{ role: 'user', content: `Correct ${langVariant} spelling and grammar only. ` + `Do not change meaning, do not answer the user, do not explain anything, and do not add content. ` + `If the text is already fine, return it unchanged. ` + `Return only the corrected text.\n\n` + original }] }; const res = await fetch(v.aiUrl, { method: 'POST', headers, body: JSON.stringify(payload) }); const j = await res.json(); let corrected = ''; if (j && typeof j.text === 'string') corrected = j.text.trim(); else { const alt = j && j.choices && j.choices[0] && j.choices[0].message && j.choices[0].message.content; if (typeof alt === 'string') corrected = alt.trim(); } if (!corrected) return original; // Reject obvious meta/apology replies from the model if ( /i need the text you want corrected/i.test(corrected) || /please provide the text/i.test(corrected) || /i'm sorry/i.test(corrected) ) { return original; } // Reject wildly longer outputs; spellcheck should not rewrite a tiny answer into a sentence if (corrected.length > original.length + 20) {
return original;
}

return corrected;
} catch (e) {
return text;
}
}

// Thread state
// Thread state
const thread = [];

// Keep a stable session id (GTKY style)
const SID_KEY = ‘cp_sid’;
let sessionId = getParam(‘sid’, ”) || sessionStorage.getItem(SID_KEY) || ”;
if (!sessionId) {
sessionId = (crypto?.randomUUID ? crypto.randomUUID() : String(Date.now()));
sessionStorage.setItem(SID_KEY, sessionId);
}
// Ensure URL carries sid
if (!getParam(‘sid’,”)) {
const u = new URL(location.href);
u.searchParams.set(‘sid’, sessionId);
history.replaceState(null, ”, u);
}

// Per-Insight stable response_id (so each Insight keeps its own 320/329/338 chain)
function respKeyForThisInsight() {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const base = (getParam(‘insight’,”) || v.insightSequence || ‘generic’).trim();
return ‘cp_resp_id_’ + base;
}

// Prevent duplicate 329/338 emits for the same accepted user turn
let metaCommitted = false;
let endReportShown = false;
let aiTurnInProgress = false;
let aiCallCountThisTurn = 0;
let consecutiveDisengagedTurns = 0;
let stepResetAppliedThisPage = false;
const MAX_AI_CALLS_PER_TURN = 10;

function pushMsg(role, content) {
const isAssistantObject =
role === ‘assistant’ &&
content &&
typeof content === ‘object’;

const safeContent = isAssistantObject
? {
reflection: String(content.reflection || ”).trim(),
question: String(content.question || ”).trim()
}
: String(content ?? ”);

thread.push({ role, content: safeContent });

if (role === ‘user’) metaCommitted = false;

renderThread();

window.cpVars = window.cpVars || {};
window.cpVars.conversationHistory = window.cpVars.conversationHistory || [];

window.cpVars.conversationHistory.push({
role,
content: isAssistantObject
? (safeContent.question || safeContent.reflection)
: safeContent
});

if (window.cpVars.conversationHistory.length > 20) {
window.cpVars.conversationHistory.shift();
}
}
function renderThread() {
const box = qs(‘#cp-ai-thread’);
if (!box) return;

box.innerHTML = ”;

const USER_NAME = getParam(‘nname’, ”) || ‘You’;
const COACH_NAME = ‘AI Coach’;

for (const m of thread) {
const isUser = (m.role === ‘user’);

if (isUser) {
const bubble = document.createElement(‘div’);
bubble.className = ‘cp-bubble cp-user’;

const head = document.createElement(‘div’);
head.className = ‘cp-msg-head cp-user-head’;
head.innerHTML = `👤 ${esc(USER_NAME)}`;
bubble.appendChild(head);

const body = document.createElement(‘div’);
body.className = ‘cp-msg-text’;
body.textContent = String(m.content ?? ”);
bubble.appendChild(body);

box.appendChild(bubble);
continue;
}

const c = (typeof m.content === ‘object’)
? m.content
: { reflection: ”, question: String(m.content ?? ”) };

// reflection block (outside bubble)

if (c.reflection) {
const r = document.createElement(‘div’);
r.className = ‘cp-reflection-block’;

const heading = document.createElement(‘div’);
heading.className = ‘cp-msg-head cp-ai-head cp-reflection-heading’;
heading.textContent = ‘Consider this…’;

const reflectionBody = document.createElement(‘div’);
reflectionBody.className = ‘cp-reflection-body’;

const icon = document.createElement(‘div’);
icon.className = ‘cp-reflection-icon’;
icon.textContent = ‘⚡’;

const text = document.createElement(‘div’);
text.className = ‘cp-reflection-text’;
text.textContent = c.reflection;

reflectionBody.appendChild(icon);
reflectionBody.appendChild(text);

r.appendChild(heading);
r.appendChild(reflectionBody);

box.appendChild(r);
}
// coach bubble (question only)
const bubble = document.createElement(‘div’);
bubble.className = ‘cp-bubble cp-assistant’;

const head = document.createElement(‘div’);
head.className = ‘cp-msg-head cp-ai-head’;
head.innerHTML = `⚡ ${esc(COACH_NAME)}`;
bubble.appendChild(head);

const body = document.createElement(‘div’);
body.className = ‘cp-msg-text’;
body.textContent = c.question || ”;
bubble.appendChild(body);

box.appendChild(bubble);
}

box.scrollTop = box.scrollHeight;
}

function hasUserText() {
return thread.some(m => m.role === ‘user’ && (m.content || ”).trim().length > 0);
}

function buildTranscript(maxChars = 6000) {
const lines = [];

for (const m of thread) {
if (!m?.content) continue;

if (m.role === ‘user’) {
lines.push(`You: ${String(m.content)}`);
continue;
}

if (m.role === ‘assistant’) {
if (typeof m.content === ‘object’) {
if (m.content.reflection) {
lines.push(`Reflection: ${String(m.content.reflection)}`);
}
if (m.content.question) {
lines.push(`AI Coach: ${String(m.content.question)}`);
}
} else {
lines.push(`AI Coach: ${String(m.content)}`);
}
}
}

let t = lines.join(‘\n’);
if (t.length > maxChars) t = t.slice(t.length – maxChars);
return t;
}

async function cpAiFetch(label, url, options) {
aiCallCountThisTurn++;

console.log(‘AI CALL’, aiCallCountThisTurn, label);

if (aiCallCountThisTurn > MAX_AI_CALLS_PER_TURN) {
throw new Error(‘AI call limit exceeded for this turn’);
}

return fetch(url, options);
}

function getRelevantPriorUserSignal(currentUserText = ”) {
const current = String(currentUserText || ”).trim();

const userTurns = thread
.filter(m => m && m.role === ‘user’)
.map(m => String(m.content || ”).trim())
.filter(Boolean);

// The latest user turn is the one we are responding to now, so remove it.
if (current && userTurns.length && userTurns[userTurns.length – 1] === current) {
userTurns.pop();
}

// Pick the most recent substantial prior signal only.
for (let i = userTurns.length – 1; i >= 0; i–) {
const t = userTurns[i];
if (t.length >= 20) return t;
}

return ”;
}

async function decidePriorSignalMention(userText, evalResult) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return ”;

const candidateSignal = getRelevantPriorUserSignal(userText);
if (!candidateSignal) return ”;

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const previousCoachQuestion = (() => {
for (let i = thread.length – 1; i >= 0; i–) {
const m = thread[i];
if (!m || m.role !== ‘assistant’) continue;

if (typeof m.content === ‘object’) {
const q = String(m.content.question || ”).trim();
if (q) return q;
} else {
const q = String(m.content || ”).trim();
if (q) return q;
}
}
return ”;
})();

const insightQuestion = String(v.coachFields?.insightQuestion || v.insight?.question || ”).trim();

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{
role: ‘system’,
content:
‘You are deciding whether the coach should briefly refer to one earlier user statement when asking the next question.\n’ +
‘\n’ +
‘Return ONLY valid JSON in this exact form:\n’ +
‘{“use_prior_signal”:true|false,”prior_signal”:”…”}\n’ +
‘\n’ +
‘Rules:\n’ +
‘- This is optional.\n’ +
‘- Use prior material ONLY if it directly helps the current question within the current Insight.\n’ +
‘- The prior signal must be clearly relevant to the same live line of inquiry.\n’ +
‘- Do NOT use prior material just because it is interesting.\n’ +
‘- Do NOT use prior material if it would widen the topic, change topic, or make the coach sound vague.\n’ +
‘- Do NOT rewrite the prior signal into analysis.\n’ +
‘- If used, return the exact prior signal or a very lightly trimmed version of it.\n’ +
‘- If not clearly useful, return {“use_prior_signal”:false,”prior_signal”:””}’
},
{
role: ‘user’,
content:
‘CURRENT INSIGHT QUESTION:\n’ +
insightQuestion + ‘\n’ +
‘\n’ +
‘LAST AI COACH QUESTION:\n’ +
previousCoachQuestion + ‘\n’ +
‘\n’ +
‘GATE RESULT:\n’ +
JSON.stringify(evalResult) + ‘\n’ +
‘\n’ +
‘CURRENT USER REPLY:\n’ +
String(userText || ”).trim() + ‘\n’ +
‘\n’ +
‘CANDIDATE PRIOR USER SIGNAL:\n’ +
candidateSignal
}
]
};

try {
const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});

const j = await res.json();
const raw = String(j.text || j.reply || j.content || ”).trim();
const cleaned = raw.replace(/“`json/g, ”).replace(/“`/g, ”).trim();
const parsed = JSON.parse(cleaned);

if (!parsed || !parsed.use_prior_signal) return ”;
return String(parsed.prior_signal || ”).trim().slice(0, 220);
} catch (err) {
console.log(‘PRIOR SIGNAL DECISION ERROR:’, err);
return ”;
}
}

function renderEndOfInsightReport(summaryText = ”, insightText = ”, opts = {}) { const box = qs(‘#cp-end-report’);
if (!box) return;

const summary = String(summaryText || ”).trim();
const insight = String(insightText || ”).trim();
const loading = !!opts.loading;

if (!summary && !insight && !loading) {
box.innerHTML = ”;
box.style.display = ‘none’;
return;
}

if (loading) {
box.innerHTML = `

End of Insight

Please wait while AI Coach prepares a summary for you…

`;
box.style.display = ‘block’;
return;
}

box.innerHTML = `

End of Insight

${summary ? `

${esc(summary)}

` : “}
${insight ? `

My insight on this: ${esc(insight)}

` : “}

`;
box.style.display = ‘block’;

const resumeBtn = qs(‘#cp-end-report-resume’, box);
const nextInsightBtn = qs(‘#cp-end-report-next’, box);

if (resumeBtn) {
resumeBtn.addEventListener(‘click’, () => {
endReportShown = false;
nextConfirmedOverride = false;
renderEndOfInsightReport(”, ”);

const inputWrap = qs(‘.cp-input’);
if (inputWrap) inputWrap.style.display = ”;

const sendBtnEl = qs(‘#cp-ai-send’);
const nextBtnEl = qs(‘#cp-ai-next’);
const ctaTextEl = qs(‘#cp-ai-cta-status’);

if (sendBtnEl) {
sendBtnEl.style.display = ”;
sendBtnEl.disabled = true;
}

if (nextBtnEl) {
nextBtnEl.style.display = ”;
nextBtnEl.hidden = false;
nextBtnEl.disabled = false;
nextBtnEl.removeAttribute(‘disabled’);
nextBtnEl.textContent = ‘End’;
}

if (ctaTextEl) {
ctaTextEl.textContent = ‘Awaiting your response…’;
}

clearNudge();
scheduleNudge();
});
}

if (nextInsightBtn) {
nextInsightBtn.addEventListener(‘click’, () => {
endReportShown = false;
triggerNextNavigation();
});
}
}

async function showEndOfInsightReport() {
endReportShown = true;
nextConfirmedOverride = false;

renderEndOfInsightReport(”, ”, { loading: true });

const summary = await summariseThread();
const endInsight = await generateEndOfInsightInsight(summary);

await saveConversationSummary({ summary });

await saveNow({
status: ‘Ended’,
summary
});

renderEndOfInsightReport(summary, endInsight);

const nextBtnEl = qs(‘#cp-ai-next’);
if (nextBtnEl) {
nextBtnEl.disabled = true;
nextBtnEl.style.display = ‘none’;
}
const inputWrap = qs(‘.cp-input’);
if (inputWrap) inputWrap.style.display = ‘none’;
}

function cpBaseMeta() {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
return {
userpass: String(v.userpass || getParam(‘userpass’,”) || ”).trim(),
session: sessionId,
user_id: String(window.currentWpUserId || ”),
edition: String(v.edition || getParam(‘edition’,”) || ”),
kind: ‘insight’,
insight_id: String(getParam(‘insight’,”) || v.insightSequence || ”),
linked_insight_key: String(getParam(‘insight’,”) || v.insightSequence || ”)
};
}

async function postSaveMemory(payload) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.saveUrl || (!v.token && !v.restNonce)) return;

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

return fetch(v.saveUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload),
keepalive: true
});
}

// —- 320 (Responses) saver (same purpose as your old saveNow) —-
async function saveNow(payload = {}) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.saveUrl || (!v.token && !v.restNonce)) return;
if (!hasUserText()) return;

const RESP_KEY = respKeyForThisInsight();
let responseId = sessionStorage.getItem(RESP_KEY);
if (!responseId) {
responseId = (crypto?.randomUUID ? crypto.randomUUID() : String(Date.now()));
sessionStorage.setItem(RESP_KEY, responseId);
}

// derive last user / last AI
let lastUser = ”, lastAI = ”;
for (let i = thread.length – 1; i >= 0; i–) {
const m = thread[i];
if (!m || !m.content) continue;

if (!lastUser && m.role === ‘user’) {
lastUser = String(m.content || ”).trim();
}

if (!lastAI && m.role === ‘assistant’) {
if (typeof m.content === ‘object’) {
lastAI = String(m.content.question || ”).trim();
} else {
lastAI = String(m.content || ”).trim();
}
}

if (lastUser && lastAI) break;
}

const body = Object.assign({}, cpBaseMeta(), {
response_id: responseId,
dialogue: buildTranscript(),
response_sequence: thread.filter(m => m.role === ‘user’).length,
status: ‘Live’,
insight_sequence: v.insightSequence || getParam(‘insight’,”) || ”,
tone: v.tone || getParam(‘tone’,’direct’) || ‘direct’,
}, payload);

if (!(‘user_input’ in body) && lastUser) body.user_input = lastUser;
if (!(‘ai_reply’ in body) && lastAI) body.ai_reply = lastAI;

// strip empties
[‘ai_reply’,’summary’,’dialogue’,’user_input’].forEach(k => {
if (k in body && String(body[k]).trim() === ”) delete body[k];
});

await postSaveMemory(body);
}

// —- Summary generator (used to feed 329/338 + stored on 320) —-
async function summariseThread() {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return ”;

// Use only the recent tail to keep it cheap + focused
const transcript = buildTranscript(2500);

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const payload = {
model: ‘gpt-4o’,
temperature: 0.2,
messages: [{
role: ‘user’,
content:
`Write a concise, Insight-specific coach summary of the conversation so far.\n` +
`\n` +
`OBJECTIVE:\n` +
`- State what you have noticed about the user, speaking directly to them.\n` +
`\n` +
`VOICE:\n` +
`- Write directly to the user using “you”.\n` +
`- Do NOT refer to “the user”.\n` +
`- Do NOT describe them from the outside.\n` +
`\n` +
`FORM:\n` +
`- 2–5 sentences.\n` +
`- Sound like a coach reflecting back what you have observed.\n` +
`\n` +
`CONSTRAINTS:\n` +
`- Stay grounded in what they actually said.\n` +
`- Focus on what they revealed, tensions, values, and motivations.\n` +
`- Do NOT generalise beyond the evidence.\n` +
`- Do NOT give generic productivity advice.\n` +
`- Do NOT use therapeutic or diagnostic language.\n` +
`\n` +
`TRANSCRIPT:\n${transcript}`
}]
};

const res = await fetch(v.aiUrl, { method: ‘POST’, headers, body: JSON.stringify(payload) });
const j = await res.json();
const text = (j && (j.text || j.reply || j.content)) ? String(j.text || j.reply || j.content) : ”;
return text.trim();
}

async function generateEndOfInsightInsight(summaryText) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return ”;

const transcript = buildTranscript(3000);
const insightQuestion = String(v.coachFields?.insightQuestion || v.insight?.question || ”).trim();
const insightText = String(v.insight?.text || ”).trim().slice(0, 1200);

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const payload = {
model: ‘gpt-4o’,
temperature: 0.2,
messages: [{
role: ‘user’,
content:
`You are deciding whether the coach has enough evidence to offer one insight at the end of this Insight.\n` +
`Return ONLY valid JSON in this exact form:\n` +
`{“should_offer_insight”:true|false,”insight”:”…”}\n\n` +
`Rules:\n` +
`- The insight is optional.\n` +
`- Only offer one if the conversation provides enough evidence.\n` +
`- Base it on repeated or reinforced patterns, not one isolated sentence.\n` +
`- Stay grounded in what the user has actually shared.\n` +
`- The insight MUST show how the user’s pattern affects their ability to engage with the core idea of this Insight.\n` +
`- The Insight idea must be part of the explanation, not mentioned separately at the end.\n` +
`- Explain whether the user’s behaviour supports, limits, or complicates that idea.\n` +
`- Keep it short and direct.\n` +
`- Do NOT introduce a new theory, diagnosis, or abstraction.\n` +
`- Keep it to 1–2 sentences max.\n` +
`- If there is not enough evidence, return {“should_offer_insight”:false,”insight”:””}\n\n` +
`CURRENT INSIGHT:\n` +
`Question: ${insightQuestion}\n` +
`Core idea: ${insightText}\n\n` +
`SUMMARY:\n${String(summaryText || ”).trim()}\n\n` +
`TRANSCRIPT:\n${transcript}`
}]
};

try {
const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});

if (!parsed || !parsed.should_offer_insight) return ”;
return String(parsed.insight || ”).trim();
} catch (err) {
console.log(‘END OF INSIGHT INSIGHT ERROR:’, err);
return ”;
}
}
// —- 329 trait scorer (LLM JSON) —-
async function scoreTraitsWithLLM({ questionText, answerText, miniSummary }) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return { traits: [] };

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const system =
`You are scoring Change Pathway trait signals from ONE user answer.\n` +
`Traits: Awareness, Balance, Commitment, Drive, Engagement, Flexibility, Groundedness, Heart.\n` +
`Return ONLY valid JSON of the form:\n` +
`{“traits”:[{“trait”:”Awareness”,”quality”:”Positive|Neutral|Negative|Caution”,”confidence”:1-10,”rationale”:”…”,”quote”:”…”}]}\n` +
`Rules:\n` +
`- Max 3 traits.\n` +
`- Be conservative; if weak evidence, return []\n` +
`- quote must be exact user words (a short phrase).\n`;

const user =
`INSIGHT QUESTION:\n${questionText}\n\n` +
`USER ANSWER:\n${answerText}\n\n` +
`MINI SUMMARY:\n${miniSummary}\n`;

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{ role: ‘system’, content: system },
{ role: ‘user’, content: user }
]
};

const res = await fetch(v.aiUrl, { method: ‘POST’, headers, body: JSON.stringify(payload) });
const j = await res.json();
const raw = (j && (j.text || j.reply || j.content)) ? String(j.text || j.reply || j.content) : ”;

try {
const parsed = JSON.parse(raw);
if (parsed && Array.isArray(parsed.traits)) return parsed;
} catch {}
return { traits: [] };
}

// —- Chapter map + classifier (338) —-
async function ensureChapterMapLoaded() {
try {
if (window.cpChapterMap && Object.keys(window.cpChapterMap).length) return window.cpChapterMap;

const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const headers = {};
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

async function classifyChapterForAnswer({ questionText, answerText, summary }) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return null;

const ans = (answerText || ”).trim();
if (!ans) return null;

const map = await ensureChapterMapLoaded();
if (!map || !Object.keys(map).length) return null;

const catalogue = buildChapterCatalogue(map);

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const trimmedLastUser = (lastUser || ”).trim();
const trimmedSummary = (summary || ”).trim();
if (!trimmedLastUser && !trimmedSummary) return;

const dialogueTail = (() => {
const txt = buildTranscript(1200);
return txt.length > 800 ? txt.slice(-800) : txt;
})();

const base = Object.freeze(Object.assign({}, cpBaseMeta(), {
response_sequence: thread.filter(m => m.role === ‘user’).length,
response_id: responseId,
user_input: lastUser || ”,
}));

// Use Insight question as the “prompt text”
const questionText = String(v.coachFields?.insightQuestion || v.insight?.question || ”).trim();

// (1) 329 traits (append-only)
const traitSignals = await scoreTraitsWithLLM({
questionText,
answerText: lastUser,
miniSummary: trimmedSummary || ”
});

const traits = Array.isArray(traitSignals?.traits) ? traitSignals.traits : [];
for (const t of traits) {
if (!t || !t.trait) continue;

// normalise confidence to 1–10 number
let conf = Number(t.confidence);
if (!Number.isFinite(conf)) conf = 7;
conf = Math.max(1, Math.min(10, Math.round(conf)));

const allowedQual = [‘Positive’,’Neutral’,’Negative’,’Caution’];
const q = String(t.quality || ‘Neutral’).trim();
const qNorm = q ? (q[0].toUpperCase() + q.slice(1).toLowerCase()) : ‘Neutral’;
const quality = allowedQual.includes(qNorm) ? qNorm : ‘Neutral’;

const traitPayload = Object.freeze({
…base,
append_only: true,
framework: ‘Change Pathway’,
trait: String(t.trait || ”).trim(),
quality,
confidence: conf,
rationale: String(t.rationale || ”).trim().slice(0, 300) || trimmedLastUser.slice(0, 300),
quote: String(t.quote || ”).trim() || trimmedLastUser,
dialogue_tail: dialogueTail
});

try { await postSaveMemory(traitPayload); } catch {}
}

// (2) 338 chapter (append-only, 0 or 1)
const chapterDecision = await classifyChapterForAnswer({
questionText,
answerText: lastUser,
summary: trimmedSummary || ”
});

if (chapterDecision) {
const selectedQuotes = (() => {
const s = (lastUser || ”).split(/(?<=[.!?])\s+/).map(x => x.trim()).filter(Boolean);
return s.slice(0, 3);
})();

const chapterPayload = Object.freeze({
…base,
append_only: true,
chapter_key: chapterDecision.chapter_key,
matched_terms: chapterDecision.matched_terms || [],
quality: chapterDecision.quality || ‘Neutral’,
confidence: Math.max(1, Math.min(10, Math.round(Number(chapterDecision.confidence) || 8))),
rationale: trimmedSummary
? trimmedSummary.replace(/^\s*[\u2022\-\*]+\s*/gm, ”).slice(0, 900)
: trimmedLastUser.slice(0, 300),
chapter_quote: selectedQuotes.join(‘ | ‘),
quotes: selectedQuotes,
dialogue_tail: dialogueTail
});

try { await postSaveMemory(chapterPayload); } catch {}
}

metaCommitted = true;
} catch {
// swallow: we never want meta emit failures to break the UI
}
}

function getStepConfig() {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const cf = v.coachFields || {};

const rawSteps = String(cf.aiCoachFrameworkSteps || ”)
.split(/\s*\d+\.\s+/)
.map(s => s.trim())
.filter(Boolean);

const stepKey = ‘cp_step_’ + ((v.insightSequence || getParam(‘insight’,”) || ‘generic’).trim());

// 🔧 Reset step once per page load, BEFORE any read
if (getParam(‘reset’,”) === ‘1’ && !stepResetAppliedThisPage) {
sessionStorage.removeItem(stepKey);
stepResetAppliedThisPage = true;
}

console.log(‘STEP READ:’, {
key: stepKey,
stored: sessionStorage.getItem(stepKey),
reset: getParam(‘reset’,”)
});

let currentStep = Number(sessionStorage.getItem(stepKey) || 0);
if (!Number.isFinite(currentStep) || currentStep < 0) currentStep = 0; if (rawSteps.length && currentStep >= rawSteps.length) currentStep = rawSteps.length – 1;

return {
stepKey,
steps: rawSteps,
currentStep,
completionCriteria: cf.step_completion_criteria || ”,
fallbackRoutes: cf.fallback_routes || ”,
allowedMoves: cf.allowed_moves || ”,
disallowedMoves: cf.disallowed_moves || ”,
closureRule: cf.closure_rule || ”
};
}

async function evaluateTurn(userText) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};

if (!v.aiUrl) {
return {
answered_question: false,
within_insight: true,
non_answer: false,
redirect_required: true,
advance: false,
fallback: false,
close: false
};
}

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const previousCoachQuestion = (() => {
for (let i = thread.length – 1; i >= 0; i–) {
const m = thread[i];
if (!m || m.role !== ‘assistant’) continue;

if (typeof m.content === ‘object’) {
const q = String(m.content.question || ”).trim();
if (q) return q;
} else {
const q = String(m.content || ”).trim();
if (q) return q;
}
}
return ”;
})();

const insightQuestion = String(v.coachFields?.insightQuestion || v.insight?.question || ”).trim();

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{
role: ‘system’,
content:
`You are the first-stage gate in a structured coaching dialogue.

Return ONLY valid JSON in this exact form:
{
“answered_question”: true|false,
“within_insight”: true|false,
“non_answer”: true|false,
“redirect_required”: true|false,
“advance”: true|false,
“fallback”: true|false,
“close”: true|false
}

Rules:

answered_question:
– true ONLY if the user directly answers the last AI Coach question.
– If the last AI Coach question asks for a specific example, answered_question must be true ONLY when the user gives a specific example of the thing asked for.
– If the last AI Coach question asks about interests, the answer must name or describe an interest.
– If the last AI Coach question asks about working style, the answer must describe how the user works, acts, approaches tasks, or behaves when engaged.
– A meaningful belief, pattern, or emotionally important statement does NOT count as answered_question unless it answers the actual question asked.
– Do NOT treat something as answered_question merely because it is relevant to the wider Insight theme.
– false if the user:
– answers a different question
– switches to a different part of the Insight
– gives a belief instead of the requested example
– gives an example of the wrong thing
– gives filler with no direct answer

within_insight:
– true ONLY if the reply stays within the current Insight theme
– false if it drifts into a different topic, request, or task

non_answer:
– true only for replies that are vague, evasive, minimal, or non-committal AND do not add useful material to the current line of inquiry
– examples: “I don’t know”, “not sure”, “maybe”, obvious avoidance, or empty filler
– if the reply is relevant and adds evidence, example, consequence, or pattern, non_answer must be false

redirect_required:
– true only if:
– answered_question is false
– or within_insight is false
– otherwise false

advance:
– true ONLY if answered_question is true and the reply gives enough substance to move to the next framework step.
– If answered_question is false, advance must be false.
– Do NOT advance because the reply is emotionally interesting, reflective, or relevant to the wider Insight.
– Do NOT advance if the user gives a belief when the question asked for a concrete example.

fallback:
– true only if the reply is relevant but thin, hesitant, or under-developed, and the coach should stay with the same line and gently deepen it

close:
– true ONLY if the current line of inquiry is clearly exhausted and no further depth is emerging
– otherwise false

Important:
– If redirect_required is true, then advance, fallback, and close must all be false.
– Be conservative about redirecting.
– If the reply is relevant to the same pattern or line of inquiry, do NOT redirect.
– If unsure whether the user answered the actual question, prefer redirect_required = true.`
},
{
role: ‘user’,
content:
`CURRENT INSIGHT QUESTION:
${insightQuestion}

LAST AI COACH QUESTION:
${previousCoachQuestion}

USER REPLY:
${String(userText || ”).trim()}`
}
]
};

try {
const res = await fetch(v.aiUrl, {
method:’POST’,
headers,
body: JSON.stringify(payload)
});

const j = await res.json();
const raw = j.text || j.reply || j.content || ”;
const parsed = JSON.parse(raw);

return {
answered_question: !!parsed.answered_question,
within_insight: !!parsed.within_insight,
non_answer: !!parsed.non_answer,
redirect_required: !!parsed.redirect_required,
advance: !!parsed.advance,
fallback: !!parsed.fallback,
close: !!parsed.close
};
} catch {
return {
answered_question: false,
within_insight: true,
non_answer: false,
redirect_required: true,
advance: false,
fallback: false,
close: false
};
}
}

async function classifyTurnWithAI(userText) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) {
return { turnType: ‘partial’, reflectionMode: ‘none’, focus: ’cause’ };
}

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const system =
`You are classifying the user’s latest coaching reply.\n` +
`Return ONLY valid JSON in this exact form:\n` +
`{“turnType”:”insight|example|preference|repeat|disengaged|partial”,”reflectionMode”:”none|full”,”focus”:”cause|belief|fear|tradeoff|implication”}\n` +
`\n` +
`Definitions:\n` +
`- insight: the user expresses genuine self-understanding, such as a belief, fear, trade-off, assumption, or personal explanation.\n` +
`- example: the user gives a concrete instance or past event.\n` +
`- preference: the user states what they prefer, tend to choose, value, or prioritise.\n` +
`- repeat: the user mainly repeats an earlier point without meaningful new information.\n` +
`- disengaged: the user avoids, refuses, shrugs off, or gives very low-engagement input.\n` +
`- partial: the user gives some relevant content but not enough to count as one of the above.\n` +
`\n` +
`REFLECTION CONTROL RULE (CRITICAL):\n` +
`- Reflection is rare. Most turns should NOT produce a reflection.\n` +
`- Only allow reflection when the user reveals a clear belief, internal logic, fear, trade-off, or meaningful implication.\n` +
`- Do NOT reflect simple preferences, behaviours, examples, or surface statements.\n` +
`- Do NOT reflect if the insight is already obvious from the user’s words.\n` +
`- Do NOT reflect if it would only restate or tidy what the user said.\n` +
`- If in doubt, choose “none”.\n` +
`- Reflection must only be used when it adds a genuinely new perspective.\n` +
`\n` +
`Examples where reflection MUST be “none”:\n` +
`- “I like business videos”\n` +
`- “I stayed in my job for the pay”\n` +
`- “I usually play it safe”\n` +
`- any simple example without interpretation\n` +
`\n` +
`Examples where reflection MAY be “full”:\n` +
`- the user links money to identity, respect, or worth\n` +
`- the user reveals a hidden assumption or belief\n` +
`- the user exposes a tension or internal conflict\n` +
`\n` +
`Examples where reflectionMode should usually be “none”:\n` +
`- “I like stability.”\n` +
`- “I usually avoid conflict.”\n` +
`- “I chose the safer option.”\n` +
`- “I tend to overthink things.”\n` +
`- a concrete example with no real interpretation\n` +
`\n` +
`Examples where reflectionMode may be “full”:\n` +
`- the user reveals a belief, fear, trade-off, or implication that was not previously explicit\n` +
`- the user links something meaningful with danger, guilt, pressure, or loss\n` +
`- the user exposes an internal conflict with real consequences\n` +
`\n`;

const user =
`PREVIOUS AI COACH QUESTION:\n${previousCoachQuestion}\n\n` +
`USER REPLY:\n${String(userText || ”).trim()}\n\n` +
`RECENT TRANSCRIPT:\n${transcript}\n`;

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{ role: ‘system’, content: system },
{ role: ‘user’, content: user }
]
};

try {
const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});

const j = await res.json();
const raw = (j && (j.text || j.reply || j.content)) ? String(j.text || j.reply || j.content) : ”;

console.log(‘TURN CLASSIFICATION RAW:’, raw);

const parsed = JSON.parse(raw);

const allowedTypes = [‘insight’, ‘example’, ‘preference’, ‘repeat’, ‘disengaged’, ‘partial’];
const allowedReflectionModes = [‘none’, ‘full’];
const allowedFocus = [’cause’, ‘belief’, ‘fear’, ‘tradeoff’, ‘implication’];

const turnType = allowedTypes.includes(parsed.turnType) ? parsed.turnType : ‘partial’;
const reflectionMode = allowedReflectionModes.includes(parsed.reflectionMode) ? parsed.reflectionMode : ‘none’;
const focus = allowedFocus.includes(parsed.focus) ? parsed.focus : ’cause’;

console.log(‘TURN CLASSIFICATION PARSED:’, { turnType, reflectionMode, focus });

return { turnType, reflectionMode, focus };
} catch (err) {
console.log(‘TURN CLASSIFICATION ERROR:’, err);
return { turnType: ‘partial’, reflectionMode: ‘none’, focus: ’cause’ };
}
}

async function planReflection(userText, replyDecision) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return null;

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const transcript = buildTranscript(2200);
const cleanUserText = String(userText || ”).trim();

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{
role: ‘system’,
content:
`You are planning a coaching reflection.

Return ONLY valid JSON in this exact form:
{
“should_reflect”: true|false,
“pattern”: “…”,
“subject_type”: “self|external”,
“lens”: “cost|shift|tension|self|behaviour”
}

Rules:
– Decide first whether a reflection is genuinely warranted.
– Only reflect if the user has revealed something meaningfully new.
– Do NOT approve a reflection if it would only paraphrase the user’s words.
– Do NOT write the reflection itself.
– Use ONLY what the user has actually said.
– Do NOT infer causes, motives, or history that are not explicit.
– Preserve the direction of causality exactly as stated.
– Keep “pattern” short, literal, and concrete.
– Extract the user’s full pattern, not just a final cause-effect fragment.
– If the user expresses a sequence or contrast (e.g. “X but then Y, so Z”), keep all important parts.
– If reflection is not warranted, return:
{“should_reflect”:false,”pattern”:””,”subject_type”:”external”,”lens”:”behaviour”}
– subject_type must be:
– “self” if the user’s trust, doubt, or reaction is directed at themselves
– “external” if it is directed at a thing, feeling, reaction, or situation

LENS SELECTION RULE:
– Choose ONE lens that best fits the user’s response:

cost:
– use when something is being cut short, limited, or not followed through

shift:
– use when there is a clear change over time (e.g. start → drop off)

tension:
– use when two forces or positions are in conflict

self:
– use when the user is describing how they relate to themselves (e.g. trust, belief)

behaviour:
– use when the pattern is mainly about repeated actions (start → stop)

– Select the most natural fit.
– Do NOT return more than one lens.`
},

{
role: ‘user’,
content:
`USER REPLY:
${cleanUserText}

CLASSIFICATION:
– turnType = ${replyDecision.turnType}
– reflectionMode = ${replyDecision.reflectionMode}
– focus = ${replyDecision.focus}

RECENT TRANSCRIPT:
${transcript}`
}
]
};

try {
const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});

const j = await res.json();
const raw = String(j.text || j.reply || j.content || ”).trim();
console.log(‘REFLECTION PLAN RAW:’, raw);

const cleaned = raw.replace(/“`json/g, ”).replace(/“`/g, ”).trim();
const parsed = JSON.parse(cleaned);

return {
should_reflect: !!parsed.should_reflect,
pattern: String(parsed.pattern || ”).trim(),
subject_type: String(parsed.subject_type || ‘external’).trim(),
lens: String(parsed.lens || ‘behaviour’).trim()
};
} catch (err) {
console.log(‘REFLECTION PLAN ERROR:’, err);
return null;
}
}

async function writeReflection(reflectionPlan) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return ”;

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const pattern = String(reflectionPlan?.pattern || ”).trim();
const subjectType = String(reflectionPlan?.subject_type || ‘external’).trim();
const lens = String(reflectionPlan?.lens || ‘behaviour’).trim();

if (!pattern) return ”;

const payload = {
model: ‘gpt-4o’,
temperature: 0.2,

messages: [
{
role: ‘system’,
content: `You are writing a short coaching reflection from a fixed plan.

Write ONLY the reflection text.

Rules:
– Be concise: 1 sentence, maximum 2.
– Stay very close to the user’s actual words.
– Do NOT generalise beyond what is clearly implied.
– Do NOT give advice, warnings, reassurance, or moral judgement.
– Do NOT explain consequences or outcomes.
– Do NOT sound like an article, teacher, or therapist.
– State the pattern, belief, tension, or link plainly.
– Keep the tone neutral, direct, and observational.
– Do not soften or protect the user’s behaviour. If a pattern is uncomfortable or contradictory, state it plainly without judgement.
– Avoid abstract words like “tension”, “dynamic”, or “pattern of behaviour”. Use concrete, everyday language.
– Do NOT wrap the reflection in quotation marks.
– If the reflection only paraphrases or restates the user’s words without adding a new angle, return an empty string.

Good example:
“It sounds like respect is closely tied to money for you.”

Bad example:
“Equating financial success with respect can create a fragile foundation for your self-worth.”

Use the structured plan as the source of truth.
Stay within this pattern only.`
},
{
role: ‘user’,
content: `Write a reflection from this plan only:

subject_type: ${subjectType}
pattern: ${pattern}
lens: ${lens}`
}
]
};

try {
const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});

const j = await res.json();
const raw = String(j.text || j.reply || j.content || ”).trim();
console.log(‘REFLECTION WRITE RAW:’, raw);
return raw;
} catch (err) {
console.log(‘REFLECTION WRITE ERROR:’, err);
return ”;
}
}

async function generateReflection(userText, replyDecision, evalResult) {
if (!evalResult || !evalResult.advance) return ”;
if (!replyDecision || replyDecision.reflectionMode !== ‘full’) return ”;

try {
const reflectionPlan = await planReflection(userText, replyDecision);

if (!reflectionPlan || !reflectionPlan.should_reflect) return ”;
if (!reflectionPlan.pattern) return ”;

console.log(‘REFLECTION PLAN PARSED:’, reflectionPlan);

return await writeReflection(reflectionPlan);
} catch (err) {
console.log(‘REFLECTION GENERATION ERROR:’, err);
return ”;
}
}
async function callAI(userText, evalResult, replyDecision, priorSignal = ”) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const payload = {
kind: ‘insight’,
userpass: v.userpass,
edition: v.edition,
insight_sequence: v.insightSequence,
tone: v.tone || ‘direct’,
mode: v.mode || null,
insight: v.insight || null,
videos: v.videos || [],

messages: [
{
role: ‘system’,
content: (() => {
const cf = v.coachFields || {};

const stepCfg = getStepConfig();
const steps = stepCfg.steps;
const currentStep = stepCfg.currentStep;
const completionCriteria = stepCfg.completionCriteria;
const fallbackRoutes = stepCfg.fallbackRoutes;
const allowedMoves = stepCfg.allowedMoves;
const disallowedMoves = stepCfg.disallowedMoves;
const closureRule = stepCfg.closureRule;

console.log(‘STEP CONFIG AT CALLAI:’, {
steps,
currentStep,
currentStepInstruction: steps[currentStep],
completionCriteria,
fallbackRoutes,
allowedMoves,
disallowedMoves,
closureRule
});

return (
`GLOBAL BEHAVIOURAL RULES (MANDATORY):\n` +
`Your job is to move the conversation forward by asking the next best question.\n` +

`STEP OVERRIDE RULE (CRITICAL):\n` +
`- The framework step takes priority over all other coaching behaviours.\n` +
`- If any rule conflicts with the current step instruction, IGNORE that rule and follow the step.\n` +
`- This includes rules about deepening, staying with the same question, using prior signals, or avoiding new angles.\n` +
`- Reflections may notice patterns, but the next question must still follow the current framework step.\n` +
`- The purpose is to guide the user through the steps, not to explore freely.\n` +
`\n` +

‘- When the user gives minimal or disengaged responses (e.g. “not sure”, “don’t know”, “no idea”) for two consecutive turns:\n’ +
‘- First, lower the cognitive load by offering a simpler or more concrete version of the current step.\n’ +
‘- Do not repeat or rephrase the same question.\n’ +
‘- If the step asks for an example, allow a small, recent, or ordinary moment instead of a meaningful or “passion”-level example.\n’ +
‘- If the user still cannot engage, offer a gentle scaffold such as “even something small counts” rather than insisting.\n’ +
‘- If the user remains disengaged after multiple attempts within the same step, do NOT continue asking for the same type of answer.\n’ +
‘- Switch the mode of the question: move from recall (“think of a time”) to recognition or reaction.\n’ +
‘- For example, ask which option feels closer to their experience, what usually happens instead, or what makes it hard to answer.\n’ +
‘- Do not escalate pressure or repeat instructions like “please answer the question”.\n’ +

‘- When the user expresses certainty or absolutism (e.g. “no downside”, “always”, “must”), do not broaden the conversation.\n’ +
‘- Still follow the current step instruction first.\n’ +
‘- Only explore limits, assumptions, or implications if that matches the current step instruction.\n’ +
‘- If the current step asks for an example, ask for an example that tests or grounds the belief.\n’ +
`\n` +

`CLASSIFICATION RESULT:\n` +
`- turnType = ${replyDecision.turnType}\n` +
`- reflectionMode = ${replyDecision.reflectionMode}\n` +
`- focus = ${replyDecision.focus}\n` +
`\n` +

`PRIOR USER SIGNAL:\n` +
`${String(priorSignal || ”).trim() || ‘NONE’}\n` +
`\n` +

`PRIOR SIGNAL RULE:\n` +
`- If PRIOR USER SIGNAL is NONE, ignore it completely.\n` +
`- If PRIOR USER SIGNAL is present, you MUST use it to shape the next question.\n` +
`- The question should clearly connect the current reply to that prior signal.\n` +
`- Do NOT ignore the prior signal when it is present.\n` +
`- Do NOT change topic.\n` +
`- Do NOT turn it into reflection or commentary.\n` +
`- Keep the reference brief and natural.\n` +
`\n` +

`QUESTION RULE (STRICT):\n` +
`- Ask ONE question only.\n` +
`- If PRIOR USER SIGNAL is present, the question MUST explicitly connect the user’s current reply to that prior signal.\n` +
`- Do NOT include any acknowledgement.\n` +
`- Do NOT repeat or summarise what the reflection has already covered.\n` +
`- Do NOT praise, interpret, or comment on the user’s response.\n` +
`- The question should move the conversation forward after the reflection, not redo the reflection.\n` +
`\n` +

`QUESTION DISCIPLINE (CRITICAL):\n` +
`- First decide whether the user has clearly answered the last AI Coach question within the current Insight.\n` +
`- If yes, move the conversation forward.\n` +
`- If partly, stay with the same question and deepen it.\n` +
`- If no, do NOT move to the most fertile point, strongest signal, or a new line of inquiry.\n` +
`- Do NOT treat loosely related material as an answer.\n` +
`- Use the reflection only to connect what the user said back to the current question.\n` +
`- Then ask a direct version of the original question again.\n` +
`\n` +

`LANGUAGE RULE:\n` +
`- Avoid abstract phrasing like “association with”, “sense of”, or “overall”.\n` +
`- Use simple, direct language.\n` +
`- Reuse the user’s exact wording for key phrases wherever possible (e.g. “talk about it”, not “share” or “discuss”).\n` +
`- Use UK English spelling (e.g. prioritise, organise, behaviour, centre).\n` +
`\n` +

`DIRECTION:\n` +
`- Stay with the current Insight and the last AI Coach question.\n` +
`- Do NOT switch to a new thread just because the user says something emotionally interesting.\n` +
`- If the user strays, redirect them back to answering the question.\n` +
`- Do not switch topics unless the user clearly answers the question and the next step requires it.\n` +
`\n` +

`PROGRESSION:\n` +
`- If the current step requires an example and one is given, move to the next step.\n` +
`- Only deepen if the example is unclear or too vague to proceed.\n` +
`- Do not continue deepening once the step requirement is satisfied.\n` +

`GENERAL:\n` +
`- Keep language direct and specific.\n` +
`\n` +

`CONTEXT CONTROL (STRICT):\n` +
`- All responses must stay within the current Insight theme.\n` +
`- All responses must relate directly to the last AI Coach question.\n` +
`- Do NOT follow the user into unrelated topics, examples, or explanations.\n` +
`- If the user response does not answer the question or strays from the Insight, explicitly redirect them back.\n` +
`- Keep the conversation focused on working through the Insight, not general discussion.\n` +
`- Do NOT engage in general ChatGPT-style tasks, advice, or unrelated problem-solving.\n` +
`\n` +

`REDIRECTION RULE (STRICT):\n` +
`- If the user’s response does not clearly relate to the last AI Coach question AND the current Insight:\n` +
`- Do NOT continue the new line of thinking.\n` +
`- Do NOT explore the new topic.\n` +
`- Briefly anchor back to the question.\n` +
`- Then ask a direct version of the original question again.\n` +
`- Keep the wording simple and grounded in the user’s language.\n` +
`\n` +

`OFF-TASK HANDLING:\n` +
`- If the user asks for something unrelated, do not comply.\n` +
`- State briefly that the focus here is the current Insight.\n` +
`- Redirect them back to the current question or theme.\n` +
`\n` +
`QUESTION ANCHOR RULE (STEP-ALIGNED):\n` +
`- The current step instruction takes priority over the previous question.\n` +
`- If the current step introduces a new dimension, you MUST shift the question to that new angle.\n` +
`- Do not stay anchored to the previous question when the step requires a transition.\n` +
`- If the user has clearly answered the previous question, move on according to the step.\n` +
`- Only restate or tighten the same question if the answer is unclear or does not meet the step requirement.\n` +
`\n` +
`QUESTION STYLE:\n` +
`- Ask about what is happening or what follows, not why it is happening.\n` +
`- Prefer concrete, present-moment questions.\n` +
`- Keep it simple and direct.\n` +
`\n` +
`QUESTION DIRECTION (CONDITIONAL):\n` +
`- Only apply these patterns if they align with the current step instruction.\n` +
`- If the current step is about a specific dimension (e.g. Purpose, Interests, Working Style), you MUST stay within that dimension.\n` +
`- Do NOT explore consequences, impacts, or implications unless the step explicitly requires it.\n` +
`- Only ask about causes if the user has already explored the experience and consequences.\n` +
`\n` +

`STEP EXECUTION RULE (CRITICAL):\n` +
`You are operating a structured coaching sequence.\n` +
`\n` +
`Current step index: ${steps.length ? (currentStep + 1) : 0} of ${steps.length}\n` +
`\n` +
`Current step instruction:\n` +
`${steps[currentStep] || ‘No step defined’}\n` +
`\n` +

`STEP COMPLETION CRITERIA:\n` +
`${completionCriteria}\n` +
`\n` +

`FALLBACK ROUTES:\n` +
`${fallbackRoutes}\n` +
`\n` +

`ALLOWED MOVES:\n` +
`${allowedMoves}\n` +
`\n` +

`DISALLOWED MOVES:\n` +
`${disallowedMoves}\n` +
`\n` +

`CLOSURE RULE:\n` +
`${closureRule}\n` +
`\n` +

`EVALUATION RESULT:\n` +
`${JSON.stringify(evalResult)}\n` +
`\n` +

`Rules:\n` +
`- Follow the current step exactly.\n` +
`- Ask ONE question that executes this step.\n` +
`- If the user has provided a clear answer or example for the current step, move to the next step.\n` +
`- Do NOT wait for a perfect or complete answer.\n` +
`- Do NOT stay on the same step just to deepen it unless the answer is vague or incomplete.\n` +
`- Do NOT skip ahead by more than one step.\n` +

`ENDING RULES:\n` +
`- Continue while new depth is emerging.\n` +
`- If no new depth, offer to move on.\n`
);
})()
},

…thread.map(m => {
if (!m) return null;

if (m.role === ‘assistant’) {
if (typeof m.content === ‘object’) {
return {
role: ‘assistant’,
content: String(m.content.question || ”).trim()
};
}
return {
role: ‘assistant’,
content: String(m.content || ”).trim()
};
}

if (m.role === ‘user’) {
return {
role: ‘user’,
content: String(m.content || ”).trim()
};
}

return null;
}).filter(m => m && m.content),

{ role: ‘user’, content: String(userText || ”).trim() }
]
};

const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});
if (!res.ok) throw new Error(`AI error ${res.status}`);
const data = await res.json();

return String(data.text || data.reply || data.content || ”).trim();
}

async function callAI_redirectOnly(userText, evalResult) {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const previousCoachQuestion = (() => {
for (let i = thread.length – 1; i >= 0; i–) {
const m = thread[i];
if (!m || m.role !== ‘assistant’) continue;

if (typeof m.content === ‘object’) {
const q = String(m.content.question || ”).trim();
if (q) return q;
} else {
const q = String(m.content || ”).trim();
if (q) return q;
}
}
return ”;
})();

const insightQuestion = String(v.coachFields?.insightQuestion || v.insight?.question || ”).trim();

const payload = {
model: ‘gpt-4o’,
temperature: 0.2,
messages: [
{
role: ‘system’,
content:
`You are redirecting a user back into a structured Insight coaching dialogue.

Return ONE question only.

Rules:
– Do NOT begin with “Please answer the question:”.
– If the user’s reply contains something meaningful or relevant, briefly acknowledge it in one short sentence.
– Do NOT explore the new topic or follow it into a new line of inquiry.
– Explain briefly why the current question is being asked.
– Clarify what kind of response would answer it.
– Re-ask the last AI Coach question in simpler, more specific wording.
– Keep it firm, calm, and conversational.
– Do NOT give advice.
– Do NOT generate a reflection.
– Keep the response within the current Insight.
– If the user is abusive, gibberish, or completely off-topic, skip the acknowledgement and calmly redirect back to the current question.`
},
{
role: ‘user’,
content:
`CURRENT INSIGHT QUESTION:
${insightQuestion}

LAST AI COACH QUESTION:
${previousCoachQuestion}

GATE RESULT:
${JSON.stringify(evalResult)}

USER REPLY:
${String(userText || ”).trim()}`
}
]
};

const res = await fetch(v.aiUrl, {
method: ‘POST’,
headers,
body: JSON.stringify(payload)
});
if (!res.ok) throw new Error(`AI error ${res.status}`);
const data = await res.json();

return String(data.text || data.reply || data.content || ”).trim();
}

async function buildCoachReply(userText, evalResult, replyDecision) {
// redirect path — no reflection, no normal question generation
if (evalResult && evalResult.redirect_required) {
const question = await callAI_redirectOnly(userText, evalResult);

return {
reflection: ”,
question: String(question || ”).trim()
};
}

const priorSignal = await decidePriorSignalMention(userText, evalResult);
console.log(‘PRIOR SIGNAL USED:’, priorSignal);

// Reflection = immediate, local, based on what the user has just said.
// It is allowed whenever the latest reply genuinely merits one.
const reflection = await generateReflection(userText, replyDecision, evalResult);

// Question generation remains separate.
const question = await callAI(userText, evalResult, replyDecision, priorSignal);

return {
reflection: String(reflection || ”).trim(),
question: String(question || ”).trim()
};
}

function renderQuoteBlocks(insight) {
const raw = (insight && insight.quote_html && String(insight.quote_html).trim() !== ”)
? String(insight.quote_html)
: (insight && insight.quote ? String(insight.quote) : ”);

if (!raw.trim()) return ”;

// normalise newlines to
so we can split consistently
const normalised = raw
.replace(/\r\n/g, ‘\n’)
.replace(/\n/g, ‘
‘);

// Split into multiple quotes on blank line / double
const parts = normalised
.split(/(?:
\s*){2,}/i)
.map(s => s.trim())
.filter(Boolean);

const blocks = parts.map(part => {
// Split the part into lines using
const lines = part
.split(//i)
.map(s => s.trim())
.filter(Boolean);

// Expect: [quoteHtml, name, role…]
const quoteHtmlRaw = lines[0] || ”;
const nameRaw = lines[1] || ”;
const roleRaw = lines.slice(2).join(‘
‘) || ”;

// Remove literal quote characters inside the first …
const quoteClean = quoteHtmlRaw
.replace(/(\s*)[“”‘]+/i, ‘$1’)
.replace(/[””‘]+(\s*<\/strong>)/i, ‘$1’);

// Allow only basic inline tags, convert any stray newlines to
const quoteHtml = safeBasicHtml(quoteClean);
const nameHtml = safeBasicHtml(nameRaw);
const roleHtml = safeBasicHtml(roleRaw);

return `

${quoteHtml}

${nameRaw ? `

${nameHtml}

` : “}
${roleRaw ? `

${roleHtml}

` : “}

`;
}).join(”);

return `

${blocks}

`;
}

function buildInsightBodyHtml(insight) {
// Prefer text_html if present (Formidable may already provide basic HTML)
const rawHtml = (insight.text_html && String(insight.text_html).trim() !== ”)
? String(insight.text_html).trim()
: ”;

const rawText = (!rawHtml && insight.text) ? String(insight.text || ”).trim() : ”;

// Convert plain text into

paragraphs (split on blank lines)
function textToParagraphs(t) {
const paras = t
.replace(/\r\n/g, ‘\n’)
.split(/\n\s*\n+/)
.map(s => s.trim())
.filter(Boolean);

return paras.map(p => `

${esc(p).replace(/\n/g, ‘
‘)}

`).join(”);
}

// If HTML already contains

, keep it; otherwise wrap into

function normaliseHtmlToParagraphs(h) {
const hasP = /<\s*p[\s>]/i.test(h);
if (hasP) return h;

// If it’s HTML but not paragraphised, treat line breaks as paragraphs
const tmp = h
.replace(/\r\n/g, ‘\n’)
.replace(//gi, ‘\n’)
.split(/\n\s*\n+/)
.map(s => s.trim())
.filter(Boolean);

return tmp.map(p => `

${p}

`).join(”);
}

let bodyHtml = rawHtml ? normaliseHtmlToParagraphs(rawHtml) : (rawText ? textToParagraphs(rawText) : ”);
if (!bodyHtml) return ”;

// One restrained pull-quote (auto inserted after first paragraph).
// Prefer a dedicated field if you add one later; otherwise extract from this Insight’s own text.
function firstGoodSentenceFromText(t) {
const s = String(t || ”)
.replace(/\s+/g, ‘ ‘)
.trim();

if (!s) return ”;

// Split into sentences conservatively.
const parts = s.split(/(?<=[.!?])\s+/).map(x => x.trim()).filter(Boolean);

// Pick the first “good” sentence: not tiny, not massive, not a generic opener.
for (const p of parts) {
const clean = p.replace(/^[““”]+|[““”]+$/g, ”).trim();
if (clean.length < 35) continue; if (clean.length > 140) continue;
return clean;
}

// Fallback: take a clean slice.
return s.slice(0, 120).replace(/^[““”]+|[““”]+$/g, ”).trim();
}

const pullQuoteField =
insight?.pull_quote ??
insight?.pullQuote ??
insight?.[‘Pull quote’] ??
insight?.[‘Pull Quote’] ??
”;

// Use text_html stripped-ish fallback via rawText when available; if HTML-only, we still try via plain text.
const sourceTextForQuote = rawText || String(insight?.text || ”).trim();

const pullQuote = String(pullQuoteField || ”).trim() || firstGoodSentenceFromText(sourceTextForQuote);

if (pullQuote && /<\/p>/i.test(bodyHtml)) {
bodyHtml = bodyHtml.replace(
/<\/p>/i,
`

“

${esc(pullQuote)}

`
);
}

return bodyHtml;
}

function renderInsight(ctx) {
const root = qs(‘#cp-insight-root’);
if (!root) return;

const page = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const insight = ctx.insight || {};
const videos = ctx.videos || [];

const banner = ctx.active?.entry_id
? `

You have an active conversation open. Finish it before starting another Insight.

`
: ”;

const videoHtml = videos.map((v, idx) => {
const start = v.clip_start ? parseInt(v.clip_start, 10) : null;
const end = v.clip_end ? parseInt(v.clip_end, 10) : null;

const src = youtubeEmbedUrl(v.address, start, end);
if (!src) return ”;

const title = (v.clip_title || ”).trim();
const speaker = (v.heading || ”).trim();

// Use curated Tab invite text from Form 303 field [7205] when present
const tabInvite =
String(
v.tab_invite_text ??
v[‘Tab invite text’] ??
v[‘7205’] ??
”
).trim();

// Fallback to prior auto-text if the curated field is missing/blank
const affordance = tabInvite ||
((speaker && title) ? `Watch ${speaker} speak about “${title}”`
: (speaker) ? `Watch ${speaker} speak`
: (title) ? `Watch video about “${title}”`
: `Watch video`);

const detId = `cp-video-${idx}`;

return `

${esc(affordance)}

<br />

${title ? `

${esc(title)}

` : ”}

`;
}).join(”);

const tailoredHtml = ctx.tailored_html || ”;

// AI Coach heading/subheading: allow future per-user / per-insight overrides from the context API
// AI Coach heading/subheading: allow future per-user / per-insight overrides from the context API
const coachHeading = String(
ctx.coach_heading ||
ctx.coachHeading ||
ctx.tailored_coach_heading ||
ctx.tailoredCoachHeading ||
‘Your Turn.’
).trim() || ‘Your Turn.’;

// Show the default “Share your thoughts…” hint only once per browser session
const DEFAULT_COACH_SUB = ‘Share your thoughts here and I (your AI Coach) will talk them through with you.’;
const introKey = ‘cp_insight_intro_shown’;
const showIntroHint = !sessionStorage.getItem(introKey);
if (showIntroHint) sessionStorage.setItem(introKey, ‘1’);

// If the context API provides a coach subheading, always show it.
// Otherwise, show the default hint only once.
const coachSubFromCtx = String(
ctx.coach_sub ||
ctx.coachSub ||
ctx.tailored_coach_sub ||
ctx.tailoredCoachSub ||
”
).trim();

const coachSub = coachSubFromCtx || (showIntroHint ? DEFAULT_COACH_SUB : ”);
const coachSubIsIntro = (!coachSubFromCtx && showIntroHint);

root.innerHTML = `

${banner}

${(() => {
const t =
ctx?.chapterMeta?.title ||
ctx?.chapter_meta?.title ||
ctx?.insight?.chapterMeta?.title ||
ctx?.insight?.chapter_meta?.title ||
ctx?.insight?.chapter_title ||
ctx?.insight?.chapterTitle ||
”;

// Prefer the explicit chapter number if present; otherwise derive from Insight sequence “1.1” → “1”
const n =
ctx?.chapterMeta?.chapter_number ||
ctx?.chapter_meta?.chapter_number ||
ctx?.insight?.chapterMeta?.chapter_number ||
ctx?.insight?.chapter_meta?.chapter_number ||
ctx?.insight?.chapter_number ||
”;

const title = String(t || ”).trim();
let num = String(n || ”).trim();

if (!num) {
const seq = String(page.insightSequenceNumber || ”).trim();
if (seq && seq.includes(‘.’)) num = seq.split(‘.’)[0].trim();
}

if (!title && !num) return ”;

return `

${num ? `Chapter ${esc(num)}${title ? `: ${esc(title)}` : “}` : `${esc(title)}`}

`;
})()}

${(() => {
const seq = String(page.insightSequenceNumber || ”).trim(); // e.g. “1.1”
const ttl = String(insight.title || ”).trim();
const full = (seq ? `${seq} ` : ”) + ttl; // “1.1 Follow Your Passion?”
return `

${esc(full)}

`;
})()}

${renderQuoteBlocks(insight)}

${tailoredHtml ? `

${tailoredHtml}

` : ”}
${videoHtml ? `

${videoHtml}

` : ”}

${buildInsightBodyHtml(insight)}

${esc(coachHeading)}

${esc(coachSub)}

Awaiting your response…

`;

// Video: only load iframe when opened; unload when closed (prevents “audio keeps playing”)
const videoDetails = root.querySelectorAll(‘.cp-video-details’);
videoDetails.forEach(det => {
const iframe = det.querySelector(‘iframe.cp-video’);
if (!iframe) return;

const load = () => {
if (!iframe.src) iframe.src = iframe.getAttribute(‘data-src’) || ”;
};
const unload = () => {
iframe.src = ”;
};

// If it starts open for any reason, load it
if (det.open) load();

det.addEventListener(‘toggle’, () => {
if (det.open) load();
else unload();
});
});

// Safety: if user navigates away mid-play, blank all iframes
window.addEventListener(‘beforeunload’, () => {
root.querySelectorAll(‘iframe.cp-video’).forEach(f => { f.src = ”; });
});

// — Wire collapsible videos (arrow state handled by CSS; this handles loading + stopping audio) —
(function wireVideos(){
const detailsEls = root.querySelectorAll(‘details.cp-video-details’);
if (!detailsEls || !detailsEls.length) return;

function closeAllIframes() {
detailsEls.forEach(d => {
const iframe = d.querySelector(‘iframe.cp-video’);
if (!iframe) return;
// remember src if it was ever set
if (!iframe.dataset.src && iframe.getAttribute(‘src’)) {
iframe.dataset.src = iframe.getAttribute(‘src’);
}
iframe.setAttribute(‘src’, ”);
});
}

detailsEls.forEach(d => {
const iframe = d.querySelector(‘iframe.cp-video’);
if (!iframe) return;

// If someone saved older HTML with src set, normalise into data-src
const existingSrc = iframe.getAttribute(‘src’);
if (existingSrc && existingSrc.trim() && (!iframe.dataset.src || !iframe.dataset.src.trim())) {
iframe.dataset.src = existingSrc.trim();
iframe.setAttribute(‘src’, ”);
}

// If it starts open, load immediately
if (d.open && iframe.dataset.src) {
iframe.setAttribute(‘src’, iframe.dataset.src);
}

d.addEventListener(‘toggle’, () => {
if (d.open) {
// opening: load this one
if (iframe.dataset.src && !iframe.getAttribute(‘src’)) {
iframe.setAttribute(‘src’, iframe.dataset.src);
}
} else {
// closing: stop audio by unloading
iframe.setAttribute(‘src’, ”);
}
});
});

// If the user navigates away / closes the tab, kill any running audio.
window.addEventListener(‘pagehide’, closeAllIframes);
window.addEventListener(‘beforeunload’, closeAllIframes);
})();

window.addEventListener(‘scroll’, () => {
// only try to schedule if we’re in “awaiting response” state
if (!String(coachState?.draft || ”).trim()) scheduleNudge();
}, { passive: true });

// Wire input (REPLACEMENT BLOCK)
const sendBtn = qs(‘#cp-ai-send’);
const nextBtn = qs(‘#cp-ai-next’);
const ta = qs(‘#cp-ai-input’);
const ctaText = qs(‘#cp-ai-cta-status’);

const nudgeBtn = qs(‘#cp-ai-nudge’);
const nudgeBox = qs(‘#cp-ai-nudge-options’);

let nudgeTimer = null;
let nudgeShown = false;
let nudgeOpen = false;

function clearNudge() {
if (nudgeTimer) clearTimeout(nudgeTimer);
nudgeTimer = null;

nudgeOpen = false;

if (nudgeBtn) nudgeBtn.style.display = ‘none’;
if (nudgeBox) nudgeBox.style.display = ‘none’;
}

function scheduleNudge() {
// If the options are currently visible, do not hide them on scroll.
if (nudgeOpen) return;

// Clear timer only (do not clear UI)
if (nudgeTimer) clearTimeout(nudgeTimer);
nudgeTimer = null;

if (!nudgeBtn) return;

// only if the user hasn’t started typing
if (String(coachState?.draft || ”).trim()) return;

// Only start the timer once the input area is visible on screen
const inputWrap = ta ? ta.closest(‘.cp-input’) : null;
if (!inputWrap) return;

const rect = inputWrap.getBoundingClientRect();
const inView = rect.top < (window.innerHeight * 0.85) && rect.bottom > 0;
if (!inView) return;

nudgeTimer = setTimeout(() => {
// still empty?
if (String(ta?.value || ”).trim()) return;

// still in view?
const r = inputWrap.getBoundingClientRect();
const stillInView = r.top < (window.innerHeight * 0.85) && r.bottom > 0;
if (!stillInView) return;

nudgeBtn.style.display = ”;
}, 15000);
}

if (!sendBtn || !nextBtn || !ta || !ctaText) return;

// Next is always visible from the start (your new decision)
nextBtn.style.display = ”;
nextBtn.disabled = false;

// Minimal draft state (no sufficiency/length gating)
let coachState = { draft: ” };

// When Next is clicked and the AI says “not really covered”, we require confirmation.
// This flag means “user already confirmed they want to move on anyway”.
let nextConfirmedOverride = false;

function renderCTA() {
const locked = !!(
window.cpVars &&
window.cpVars.insightPage &&
window.cpVars.insightPage.active &&
window.cpVars.insightPage.active.entry_id
);

if (locked) {
ctaText.textContent = ‘Finish your active conversation before starting another Insight.’;
sendBtn.disabled = true;
nextBtn.disabled = true;
nextBtn.style.display = ”;
nextBtn.textContent = ‘End’;
return;
}

const hasDraft = !!String((coachState && coachState.draft) || ”).trim();

// Whenever the end report is not showing, the End button must be visible
if (!endReportShown) {
nextBtn.style.display = ”;
nextBtn.textContent = ‘End’;
}

if (!hasDraft) {
// Awaiting response: End enabled, Send disabled
ctaText.textContent = ‘Awaiting your response…’;
sendBtn.disabled = true;
nextBtn.disabled = false;
scheduleNudge();
} else {
// Listening: Send enabled, End disabled
ctaText.textContent = ‘Listening…’;
sendBtn.disabled = false;
nextBtn.disabled = true;
clearNudge();
}
}

ta.addEventListener(‘input’, () => {
// Keep draft in sync (no meaning checks, no word/char counting)
coachState.draft = String(ta.value || ”);
renderCTA();
});

// —- AI check used ONLY when the user clicks Next —-
async function assessInsightCoveredForNextClick() {
const v = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
if (!v.aiUrl) return { covered: true, message: ” }; // fail-open: never block Next if AI is unavailable

const headers = { ‘Content-Type’: ‘application/json’ };
if (v.token) headers[‘X-CP-Token’] = v.token;
else if (v.restNonce) headers[‘X-WP-Nonce’] = v.restNonce;

const cf = v.coachFields || {};
const transcript = buildTranscript(3500);
// Provide the last two user turns explicitly to the monitor model
const lastTwoUser = thread
.filter(m => m.role === ‘user’)
.slice(-2)
.map(m => String(m.content || ”).trim());

const system =
`You are checking whether this Insight has been sufficiently covered to move on.\n` +
`Be conservative.\n` +
`Return ONLY valid JSON:\n` +
`{“covered”:true|false,”message”:”…”}\n` +
`- If covered=true: message may be empty.\n` +
`- If covered=false: message must briefly say what may still be worth exploring, and ask the user to confirm if they still want to move on.\n`;

const user =
`INSIGHT QUESTION:\n${cf.insightQuestion || String(v.insight?.question || ”).trim()}\n\n` +
`INSIGHT SUMMARY:\n${cf.insightSummary || ”}\n\n` +
`TRANSCRIPT:\n${transcript}\n`;

const payload = {
model: ‘gpt-4o’,
temperature: 0,
messages: [
{ role: ‘system’, content: system },
{ role: ‘user’, content: user }
]
};

const res = await fetch(v.aiUrl, { method: ‘POST’, headers, body: JSON.stringify(payload) });
const j = await res.json();
const raw = (j && (j.text || j.reply || j.content)) ? String(j.text || j.reply || j.content) : ”;

try {
const parsed = JSON.parse(raw);
if (typeof parsed.covered === ‘boolean’) {
return { covered: !!parsed.covered, message: String(parsed.message || ”).trim() };
}
} catch {}

// If the model returns anything unexpected, do not block Next
return { covered: true, message: ” };
}

// —- AI check used on SEND (before generating a reply) —-
// Goal: detect stalled / non-productive exchange and offer the SAME confirm as [Next].
// Rule: only act on TWO successive flagged user turns.
// Once offered and user declines, do NOT offer again for this Insight/session.

function showExampleNudges() {
if (!nudgeBox) return;
nudgeOpen = true;
if (nudgeTimer) { clearTimeout(nudgeTimer); nudgeTimer = null; }
const examples = [
“It feels inspiring, but also slightly unrealistic.”,
“I like the idea, but I’m not sure what my passion actually is.”,
“It sounds idealistic — life feels more complicated than that.”
];

nudgeBox.innerHTML = examples.map(e =>
`

${esc(e)}

`
).join(”);

nudgeBox.style.display = ‘flex’;

nudgeBox.querySelectorAll(‘.cp-nudge-option’).forEach(el => {
el.addEventListener(‘click’, () => {
ta.value = el.textContent;
coachState.draft = el.textContent;
clearNudge();
renderCTA();
});
});
}

if (nudgeBtn) {
nudgeBtn.addEventListener(‘click’, showExampleNudges);
}

// Try to hand off to whatever navigation is already wired.
// (We do not assume a specific navigation implementation in this file.)
function triggerNextNavigation() {
if (endReportShown) return;

// 1) Let any outer script hook it
try {
window.dispatchEvent(new CustomEvent(‘cp_ai_next’, { detail: { source: ‘cp-ai-next’ } }));
} catch {}

// 2) If we know the next Insight KEY (field 6897), construct the next URL
try {
const page = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const nextKey = String(page.nextInsightKey || ”).trim();
if (nextKey) {
const cur = new URL(window.location.href);

const u = new URL(‘/insight/’, window.location.origin);
const sp = new URLSearchParams(cur.search || ”);

// Keep existing params, but force the next Insight key
sp.set(‘userpass’, String(page.userpass || getParam(‘userpass’,”) || ”));
sp.set(‘edition’, String(page.edition || getParam(‘edition’,”) || ”));
sp.set(‘insight’, nextKey);

// Preserve these if present
const tone = String(page.tone || getParam(‘tone’,”) || ”);
const reset = String(getParam(‘reset’,”) || ”);
const sid = String(getParam(‘sid’,”) || ”);

if (tone) sp.set(‘tone’, tone);
if (reset !== ”) sp.set(‘reset’, reset);
if (sid) sp.set(‘sid’, sid);

u.search = sp.toString();
window.location.assign(u.toString());
return;
}
} catch {}

// 3) If we already know the next Insight URL, go there
try {
const page = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const nextUrl = String(page.nextInsightUrl || page.nextUrl || ”).trim();
if (nextUrl) {
window.location.assign(nextUrl);
return;
}
} catch {}

// 4) Try common “rel=next” hooks (anchor or link)
try {
const a = document.querySelector(‘a[rel=”next”][href]’);
if (a && a.href) { window.location.assign(a.href); return; }
} catch {}

try {
const l = document.querySelector(‘link[rel=”next”][href]’);
if (l && l.href) { window.location.assign(l.href); return; }
} catch {}

// 5) If we get here, we have no safe navigation target
try { window.alert(‘Next Insight link not found on this page.’); } catch {}
}

// Next handler

nextBtn.addEventListener(‘click’, async (e) => {
if (e && e.isTrusted === false) return;

if (nextBtn.disabled) return;
if (endReportShown) return;

sendBtn.disabled = true;
nextBtn.disabled = true;
ctaText.textContent = ‘Checking whether it’s a good point to move on…’;

try {
const verdict = await assessInsightCoveredForNextClick();

if (verdict.covered) {
triggerNextNavigation();
return;
}

// Hide the whole input area immediately
const inputWrap = qs(‘.cp-input’);
if (inputWrap) inputWrap.style.display = ‘none’;

// Hide the End button immediately
nextBtn.style.display = ‘none’;

await showEndOfInsightReport();
return;

} catch {
triggerNextNavigation();
} finally {
// Only restore the normal UI if we are NOT showing the end report
if (!endReportShown) {
sendBtn.disabled = false;
nextBtn.disabled = false;
renderCTA();
}
}
});

// Send handler (adds a pre-reply stall/non-response check)
sendBtn.addEventListener(‘click’, async () => {
if (aiTurnInProgress) {
console.log(‘SEND BLOCKED: already processing’);
return;
}

if (sendBtn.disabled) return;

let text = (ta.value || ”).trim();
if (!text) return;

aiTurnInProgress = true;
aiCallCountThisTurn = 0;

// Lock UI (AI working)
sendBtn.disabled = true;
nextBtn.disabled = true;
ctaText.textContent = ‘AI Coach is updating your notes’;

// Spellcheck before submit (GTKY behaviour)
text = await spellcheckLocale(text);

// Clear input + commit user message to the thread
ta.value = ”;
coachState.draft = ”;
nextConfirmedOverride = false;
endReportShown = false;
renderEndOfInsightReport(”, ”);
nextBtn.textContent = ‘End’;
nextBtn.style.display = ”;
pushMsg(‘user’, text);

try {
const userText = text;

// Classify first, so engagement requests are detected before redirect logic
const replyDecision = await classifyTurnWithAI(userText);

const isDisengagedTurn =
replyDecision &&
replyDecision.turnType === ‘disengaged’;

consecutiveDisengagedTurns = isDisengagedTurn
? consecutiveDisengagedTurns + 1
: 0;

if (consecutiveDisengagedTurns >= 2) {
pushMsg(‘assistant’, {
reflection: ”,
question: ‘This does not seem to be landing for you, so it makes sense to stop here and move on.’
});

const coachDecision = { next_model: ‘disengagement_end_insight’ };

await saveNow({
status: ‘Live’,
‘7206’: JSON.stringify(coachDecision),
‘coach decision’: JSON.stringify(coachDecision)
});

const inputWrap = qs(‘.cp-input’);
if (inputWrap) inputWrap.style.display = ‘none’;

nextBtn.style.display = ‘none’;

await showEndOfInsightReport();
return;
}

// Handle curiosity / clarification requests before the gate can redirect them
if (replyDecision && replyDecision.engagement_request) {
const explanation = await callAI_explain(userText, null, replyDecision);

pushMsg(‘assistant’, {
reflection: ”,
question: String(explanation || ”).trim()
});

const coachDecision = { next_model: ‘next_click_ai_check’ };
await saveNow({
status: ‘Live’,
‘7206’: JSON.stringify(coachDecision),
‘coach decision’: JSON.stringify(coachDecision)
});
return;
}

const evalResult = await evaluateTurn(userText);

// hard stop if redirect is required
if (evalResult && evalResult.redirect_required) {
const aiText = await buildCoachReply(userText, evalResult, replyDecision);
pushMsg(‘assistant’, aiText);

// TEMP: disabled per-turn AI scoring.
// await saveConversationSummary({ summary });
// Summary, trait scoring, and chapter classification should run at End of Insight only.

const coachDecision = { next_model: ‘next_click_ai_check’ };
await saveNow({
status: ‘Live’,
‘7206’: JSON.stringify(coachDecision),
‘coach decision’: JSON.stringify(coachDecision)
});
} else {
let reachedEndOfInsight = false;
const stepCfg = getStepConfig();
const steps = stepCfg.steps;
let currentStep = stepCfg.currentStep;

if (
evalResult &&
evalResult.advance &&
steps.length &&
currentStep < steps.length - 1 && replyDecision && ['insight', 'example', 'preference'].includes(replyDecision.turnType) ) { currentStep++; console.log('STEP WRITE:', { key: stepCfg.stepKey, value: currentStep, previousStored: sessionStorage.getItem(stepCfg.stepKey), stepsLength: steps.length }); sessionStorage.setItem(stepCfg.stepKey, String(currentStep)); reachedEndOfInsight = (currentStep >= steps.length – 1);}
const aiText = await buildCoachReply(userText, evalResult, replyDecision);
pushMsg(‘assistant’, aiText);

if (reachedEndOfInsight) {
nextConfirmedOverride = true;
}

const coachDecision = { next_model: ‘next_click_ai_check’ };
await saveNow({
status: ‘Live’,
‘7206’: JSON.stringify(coachDecision),
‘coach decision’: JSON.stringify(coachDecision)
});
}

} catch (e) {
pushMsg(‘assistant’, `Sorry — something went wrong. ${String(e.message || e)}`);
} finally {
aiTurnInProgress = false;
aiCallCountThisTurn = 0;
sendBtn.disabled = false;
nextBtn.disabled = false;
renderCTA();
}
});

// Initial UI state
sendBtn.textContent = ‘Send’;
nextBtn.textContent = ‘End’;
nextBtn.style.display = ”;
coachState.draft = String(ta.value || ”);
renderCTA();
}

async function init() {
const page = (window.cpVars && window.cpVars.insightPage) ? window.cpVars.insightPage : {};
const userpass = getParam(‘userpass’,”);
const edition = (getParam(‘edition’,’workplace’) || ‘workplace’).toLowerCase();
const insight = getParam(‘insight’,”);
const tone = (getParam(‘tone’,’direct’) || ‘direct’).toLowerCase();

page.tone = tone;

if (!userpass) {
const root = qs(‘#cp-insight-root’);
if (root) root.innerHTML = `

Missing userpass.

`;
return;
}

const headers = {};
if (page.token) headers[‘X-CP-Token’] = page.token;
else if (page.restNonce) headers[‘X-WP-Nonce’] = page.restNonce;

if (!page.contextUrl) {
const root = qs(‘#cp-insight-root’);
if (root) root.innerHTML = `

Missing cpVars.insightPage.contextUrl.

`;
return;
}

// Build context URL using ONLY the params the endpoint expects.
// (Do not forward arbitrary page params like “id” etc.)
const u = new URL(page.contextUrl, window.location.origin);
const sp = new URLSearchParams();

sp.set(‘userpass’, userpass);
sp.set(‘edition’, edition);
sp.set(‘insight’, insight || ”);
sp.set(‘tone’, tone || ‘direct’);

const reset = String(getParam(‘reset’, ”) || ”).trim();
const sid = String(getParam(‘sid’, ”) || ”).trim();

if (reset !== ”) sp.set(‘reset’, reset);
if (sid !== ”) sp.set(‘sid’, sid);

u.search = sp.toString();

const res = await fetch(u.toString(), { headers });
if (!res.ok) throw new Error(`Insight context error ${res.status}`);
const ctx = await res.json();

// store into cpVars for AI calls
page.userpass = userpass;
page.edition = edition;

// KEEP: entry-key (used for routing + saving)
page.insightSequence = insight;

// NEW: human-facing Insight Sequence number (Formidable field [6856])
// Prefer numeric key access because it’s the most reliable across payload variants.
const i = ctx?.insight || {};
const i2 = ctx?.insight_fields || ctx?.insightFields || ctx?.fields || {}; // defensive

// Helper: first non-empty value from a list of candidates
const pick = (…vals) => {
for (const v of vals) {
const s = (v === null || v === undefined) ? ” : String(v);
if (s.trim() !== ”) return s.trim();
}
return ”;
};

// NEW: sequence number from field [6856] (plus common named variants)
page.insightSequenceNumber = pick(
// numeric field key variants
i2?.[‘6856’], i?.[‘6856’],
i2?.[6856], i?.[6856],

// common human-name variants (depends how MU serialises the record)
i2?.[‘Insight Sequence’], i?.[‘Insight Sequence’],
i2?.[‘Insight Sequence field’], i?.[‘Insight Sequence field’],
i2?.insight_sequence, i?.insight_sequence,
i2?.insightSequence, i?.insightSequence
);

// Debug (only when missing): show which keys we actually got back
if (!page.insightSequenceNumber) {
console.log(‘[cp-insight] missing Insight Sequence [6856]’, {
insightKey: insight, // the entry-key from URL
insightKeys: Object.keys(i || {}).sort(),
altKeys: Object.keys(i2 || {}).sort(),
sample: {
i_6856: i?.[‘6856’] ?? i?.[6856],
i2_6856: i2?.[‘6856’] ?? i2?.[6856],
i_named: i?.[‘Insight Sequence’],
i2_named: i2?.[‘Insight Sequence’]
}
});
}

page.insight = ctx.insight;
page.videos = ctx.videos;
page.mode = ctx.mode;

// Prefer the MU-provided canonical field (ctx.insight.next).
page.nextInsightKey = pick(
i?.next,
i?.nextInsightKey,
i2?.[‘6897’], i?.[‘6897’],
i2?.[6897], i?.[6897]
);

// NEW: curated coaching rails (field names)
// (i, i2, pick already defined above)

const interventionScope =
i?.intervention_scope_v3 ??
i?.[‘Intervention Scope v3’] ??
i?.[‘7207’] ??
i?.[7207] ??
i2?.intervention_scope_v3 ??
i2?.[‘Intervention Scope v3’] ??
i2?.[‘7207’] ??
i2?.[7207] ??
”;

const aiInsightPromptV3 =
i?.ai_insight_prompt_v3 ??
i?.[‘AI Insight Prompt v3’] ??
i?.[‘7208’] ??
i?.[7208] ??
i2?.ai_insight_prompt_v3 ??
i2?.[‘AI Insight Prompt v3’] ??
i2?.[‘7208’] ??
i2?.[7208] ??
”;

const aiStepPromptV3 =
i?.ai_step_prompt_v3 ??
i?.[‘AI Step Prompt v3’] ??
i?.[‘7209’] ??
i?.[7209] ??
i2?.ai_step_prompt_v3 ??
i2?.[‘AI Step Prompt v3’] ??
i2?.[‘7209’] ??
i2?.[7209] ??
”;

// Debug (only when missing): shows what keys are actually coming back from the endpoint
// Debug (only when missing): shows what keys are actually coming back from the endpoint
if (!interventionScope || !aiInsightPromptV3 || !aiStepPromptV3) {
console.log(‘[cp-insight] missing coach rails (v3)’, {
interventionScopePresent: !!interventionScope,
aiInsightPromptV3Present: !!aiInsightPromptV3,
aiStepPromptV3Present: !!aiStepPromptV3,
insightKeys: Object.keys(i || {}).sort(),
altKeys: Object.keys(i2 || {}).sort()
});
}
console.log(‘Insight object keys:’, Object.keys(i || {}));
console.log(‘Alt insight object keys:’, Object.keys(i2 || {}));

const aiCoachFrameworkSteps =
i?.[7202] ??
i?.[‘7202’] ??
i2?.[7202] ??
i2?.[‘7202’] ??
”;

page.coachFields = {
// Core framing (must)
insightQuestion: pick(i[‘Insight Question’], i.question, i2[‘Insight Question’], i2.question),
insightSummary: pick(i[‘Insight Summary’], i2[‘Insight Summary’]),

// Primary coaching guidance (must)
coachGuidance: pick(
i[‘AI Coach – Generic advice, customised for Insight’],
i2[‘AI Coach – Generic advice, customised for Insight’]
),

// AI coaching rails (v3 only)
interventionScope: interventionScope,
aiInsightPrompt: aiInsightPromptV3,
aiStepPrompt: aiStepPromptV3,
aiCoachFrameworkSteps:
insight?.ai_coach_framework_steps ||
i?.ai_coach_framework_steps ||
i2?.ai_coach_framework_steps ||
”,

// Behaviour/process rails (must)
coachStyle: pick(i[‘Coach Style’], i2[‘Coach Style’]),
coachChunking: pick(i[‘Coach Chunking’], i2[‘Coach Chunking’]),
};

// NEW: capture Insight Guide (WE Insight Guide)
page.insightGuide = String(
ctx?.insight?.[‘WE Insight Guide’] || ”
).trim();

renderInsight(ctx);

// Seed first AI prompt with the Insight question
if (ctx?.insight?.question) {
pushMsg(‘assistant’, ctx.insight.question);
}

// Optional resume fetch (if you later wire the MU resume payload properly)
// const r = await fetch(`${v.resumeUrl}?userpass=${encodeURIComponent(userpass)}&insight=${encodeURIComponent(insight)}`, { headers });
// const rd = await r.json();
// if (rd?.resume?.dialogue) { /* parse transcript back into thread if you want */ }
}

if (document.readyState === ‘loading’) {
document.addEventListener(‘DOMContentLoaded’, init);
} else {
init();
}
})();

4. Insight JS code (with summary)

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