Дмитрий
f54c82d682
Closes brain-retro 2026-05-20 #11 — parseReasoningTag extracts opt-in <!-- reasoning: triggers="..." candidates="..." boundaries="..." --> HTML-comment from assistant text. Semicolon-separated values merged into heuristic-derived primary_rationale arrays via Set-dedupe. Conservative: tag is opt-in; heuristic still runs even when tag present (heuristic provides baseline, tag enriches). 5 new vitest tests, 309/309 GREEN. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
661 lines
25 KiB
JavaScript
661 lines
25 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Transcript parser for the brain governance observer.
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* Deterministically extracts episode fields from a Claude Code session
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* transcript (JSONL). No LLM — pure parsing.
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*
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* Scope: the last turn (from the last real user prompt to end of file) —
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* one episode == one prompt→response cycle.
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*
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* Reasoning fields (triggers_matched / candidates_considered /
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* boundaries_applied) are NOT recoverable from a transcript and stay [];
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* their capture is a separate design question (ADR-011 follow-up).
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*
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* Security Guidance #40: pure parsing — no exec/execSync.
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* Per ADR-011 §6 + spec v1.1 §5.2.1.
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*/
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import { detectChoiceProvenance, detectAskUserQuestionChoice } from './observer-choice-detector.mjs';
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const SUPERPOWERS_PREFIX = 'superpowers:';
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function parseLines(text) {
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const entries = [];
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let broken = 0;
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let total = 0;
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// quirk #101 root fix: Claude Code's transcript file accumulates duplicated
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// context-rebuild snapshots — the same entry is re-printed with the SAME
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// `uuid`. Without dedup, session_turn / task_size / events double-count and
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// session_turn becomes non-monotonic across episodes parsed at different
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// file-growth states. Keep the first occurrence per uuid; entries without a
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// uuid (synthetic test fixtures) pass through unchanged.
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const seenUuid = new Set();
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for (const line of String(text || '').split('\n')) {
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const trimmed = line.trim();
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if (!trimmed) continue;
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total += 1;
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let e;
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try {
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e = JSON.parse(trimmed);
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} catch {
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broken += 1; // broken line — counted for parse_gap, never thrown
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continue;
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}
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if (e && e.uuid) {
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if (seenUuid.has(e.uuid)) continue;
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seenUuid.add(e.uuid);
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}
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entries.push(e);
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}
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return { entries, broken, total };
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}
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// Synthetic user-role messages — NOT genuine prompts, must not be turn boundaries.
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// Skill invocation content, local slash-command output/invocation, interrupt markers
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// are recorded with role:'user' but carry no UserPromptSubmit hook context.
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const SYNTHETIC_PROMPT_MARKERS = [
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'Base directory for this skill:',
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'<local-command-stdout>',
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'<local-command-caveat>',
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'<command-name>',
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'[Request interrupted by user]',
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];
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function isSyntheticPrompt(text) {
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const t = String(text || '').trimStart();
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return SYNTHETIC_PROMPT_MARKERS.some((m) => t.startsWith(m));
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}
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// A genuine user prompt (turn boundary) — not a tool_result carrier nor a
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// synthetic skill/command/interrupt message.
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function isRealUserPrompt(entry) {
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const msg = entry && entry.message;
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if (!msg || msg.role !== 'user') return false;
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const c = msg.content;
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if (typeof c === 'string') {
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return c.trim().length > 0 && !isSyntheticPrompt(c);
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}
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if (Array.isArray(c)) {
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const hasToolResult = c.some((b) => b && b.type === 'tool_result');
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const hasText = c.some((b) => b && b.type === 'text');
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if (!hasText || hasToolResult) return false;
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const text = c
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.filter((b) => b && b.type === 'text')
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.map((b) => b.text || '')
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.join(' ');
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return !isSyntheticPrompt(text);
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}
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return false;
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}
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function findTurnStart(entries) {
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for (let i = entries.length - 1; i >= 0; i--) {
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if (isRealUserPrompt(entries[i])) return i;
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}
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return 0;
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}
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function stripSystemReminders(text) {
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return String(text || '').replace(/<system-reminder>[\s\S]*?<\/system-reminder>/g, '');
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}
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function promptText(entry) {
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const c = entry && entry.message && entry.message.content;
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if (typeof c === 'string') return stripSystemReminders(c);
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if (Array.isArray(c)) {
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const joined = c
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.filter((b) => b && b.type === 'text')
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.map((b) => b.text || '')
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.join(' ');
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return stripSystemReminders(joined);
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}
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return '';
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}
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export function classifyTask(text) {
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const t = String(text || '').toLowerCase();
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if (/обнови эталон|sync memory|обнови (?:память|memory|memory\.md)/.test(t)) return 'memory-sync';
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if (/обнови claude|правк[аи] pravila|update pravila|обнови psr|обнови tooling|нормативка/.test(t)) return 'regulatory-bump';
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if (/план|plan\b|спроектируй|design\b|brainstorm|обсудим/.test(t)) return 'planning';
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if (/\bpush\b|\bmerge\b|\bdeploy\b|\bcommit\b|\brelease\b|релиз|тегни/.test(t)) return 'release';
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if (/рефактор|refactor/.test(t)) return 'refactor';
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if (/баг|bug|почини|исправ|fix\b|сломан|broken/.test(t)) return 'bugfix';
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if (/фич|feature|добав|implement|реализ|создай|create|новый|new /.test(t)) return 'feature';
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if (/докум|readme|\bdocs?\b/.test(t)) return 'docs';
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if (/проанализ|анализ|оцени|review|examine|разбор|посмотри что/.test(t)) return 'analysis';
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if (/убери|удали|почисть|cleanup|очисти|drop\s/.test(t)) return 'cleanup';
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if (/^\s*статус\b|\bstatus\b|проверь состоян|health/.test(t)) return 'monitoring';
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if (/\?|как |что |почему|зачем|why|how |what /.test(t)) return 'question';
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return 'other';
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}
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function collectToolUse(entries) {
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const skills = [];
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const counts = {};
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const errors = [];
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const idToTool = {};
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// First pass — build id→tool name map (tool_results may reference tools across messages)
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for (const e of entries) {
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const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
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for (const b of content) {
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if (b && b.type === 'tool_use') idToTool[b.id] = b.name || 'unknown';
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}
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}
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// Second pass — accumulate counts + per-error attribution
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for (const e of entries) {
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const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
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for (const block of content) {
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if (!block || typeof block !== 'object') continue;
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if (block.type === 'tool_use') {
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const name = block.name || 'unknown';
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counts[name] = (counts[name] || 0) + 1;
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if (name === 'Skill') {
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skills.push((block.input && block.input.skill) || 'unknown');
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}
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} else if (block.type === 'tool_result' && block.is_error === true) {
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const tool = idToTool[block.tool_use_id] || 'unknown';
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const c = block.content;
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const text = typeof c === 'string' ? c
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: (Array.isArray(c) ? c.map((b) => (b && typeof b.text === 'string') ? b.text : '').join(' ') : '');
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errors.push({ tool, summary: text.slice(0, 80) });
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}
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}
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}
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return { skills, counts, errors };
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}
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const FILE_TOOLS = new Set(['Read', 'Edit', 'Write', 'MultiEdit', 'NotebookEdit']);
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/**
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* Deterministic environment factors for the turn that starts at turnStartIdx.
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* economy_level / parallel_session are scanned from the stringified turn;
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* model / post_compaction / session_turn from structural fields.
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*/
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export function extractEnvironment(allEntries, turnStartIdx) {
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const turn = allEntries.slice(turnStartIdx);
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const rawTurn = JSON.stringify(turn);
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const econ = rawTurn.match(/=== ECONOMY MODE:\s*(\d+)\s*%/);
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const economy_level = econ ? Number(econ[1]) : null;
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let model = null;
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for (const e of turn) {
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if (e && e.message && e.message.model) {
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model = e.message.model;
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break;
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}
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}
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// The transcript file accumulates duplicated context-rebuild snapshots
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// (repeated isCompactSummary entries — see feedback_environment quirk #101).
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// Counting prompts from i=0 inflates session_turn with those dupes. Count
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// from the LAST compaction before the turn: session_turn = real prompts
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// since it, which is monotonic ("turns since last compaction").
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let lastCompactIdx = -1;
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for (let i = 0; i < turnStartIdx && i < allEntries.length; i++) {
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if (allEntries[i] && allEntries[i].isCompactSummary === true) lastCompactIdx = i;
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}
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const post_compaction = lastCompactIdx >= 0;
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let session_turn = 0;
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for (let i = lastCompactIdx + 1; i <= turnStartIdx && i < allEntries.length; i++) {
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if (isRealUserPrompt(allEntries[i])) session_turn += 1;
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}
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// Only strong collision evidence — a bare mention of "parallel sessions" is
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// not a signal (best-effort per spec R2; prefer false-negative over false-positive).
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// Scope NARROWED to tool_result content (real command output / Bash stderr): prose
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// mentions in user prompts / assistant text — including analysis text that
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// references collision phrases — must not trigger. Fixes live FP (episode line 20).
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const parallel_session = /чужой staged|foreign git index|index\.lock|another git process/i.test(
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collectToolResultText(turn)
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);
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return { economy_level, model, post_compaction, session_turn, parallel_session };
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}
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/**
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* Collect text content from tool_result blocks in the turn — the only surface
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* trusted for parallel_session collision evidence (see extractEnvironment).
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* Supports both string content and the structured array form
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* (`content: [{ type: 'text', text }]`).
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*/
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function collectToolResultText(turn) {
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const parts = [];
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for (const e of turn) {
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const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
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for (const b of content) {
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if (!b || b.type !== 'tool_result') continue;
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const c = b.content;
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if (typeof c === 'string') {
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parts.push(c);
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} else if (Array.isArray(c)) {
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for (const sub of c) {
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if (sub && typeof sub.text === 'string') parts.push(sub.text);
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}
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}
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}
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}
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return parts.join('\n');
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}
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/** Task size: total tool calls + unique file paths touched (per spec §3, gap-resolution 2). */
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export function extractTaskSize(turn) {
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let tool_calls = 0;
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const files = new Set();
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for (const e of turn) {
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const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
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for (const b of content) {
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if (b && b.type === 'tool_use') {
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tool_calls += 1;
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if (FILE_TOOLS.has(b.name) && b.input) {
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const p = b.input.file_path || b.input.notebook_path;
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if (p) files.add(String(p));
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}
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}
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}
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}
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return { tool_calls, files_touched: files.size, files: [...files] };
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}
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/**
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* Token-usage aggregation across all assistant messages in the turn.
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*
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* DESIGN: returns zero-filled object (NOT null) when no `usage` data was
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* captured. Consumers cannot currently distinguish "actually 0 tokens" from
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* "no usage data" — accepted trade-off because (a) every assistant message
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* in real Claude Code transcripts has `usage` (verified B1 brain-retro
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* 2026-05-20: 6265/6265 messages with usage, 0 partial-stream), and
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* (b) `task_cost` is not yet read by analyzer/STATUS.md, so the semantic
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* gap is a future-only concern. Re-evaluate when factor matrix adds cost.
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*
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* Captures: 4 base token fields + `iterations` (extended-thinking detector)
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* + `server_tool_use.{web_search,web_fetch}_requests` counts.
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* Other usage fields (cache_creation object, inference_geo, service_tier,
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* speed) — out-of-scope for current analyzer.
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*
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* Defensive: skips entries where `usage` is not a plain object (handles
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* malformed transcript edge cases like `"usage": 42`).
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*/
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export function extractTokenUsage(turn) {
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let input = 0, output = 0, cache_read = 0, cache_creation = 0;
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let web_search = 0, web_fetch = 0, iterations = 0;
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for (const e of turn || []) {
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const u = e && e.message && e.message.usage;
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if (!u || typeof u !== 'object') continue;
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input += u.input_tokens || 0;
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output += u.output_tokens || 0;
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cache_read += u.cache_read_input_tokens || 0;
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cache_creation += u.cache_creation_input_tokens || 0;
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iterations += u.iterations || 0;
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if (u.server_tool_use) {
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web_search += u.server_tool_use.web_search_requests || 0;
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web_fetch += u.server_tool_use.web_fetch_requests || 0;
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}
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}
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return {
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input_tokens: input,
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output_tokens: output,
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cache_read_input_tokens: cache_read,
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cache_creation_input_tokens: cache_creation,
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web_search_requests: web_search,
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web_fetch_requests: web_fetch,
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iterations,
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};
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}
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/**
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* For each AskUserQuestion toolUseResult in the turn, emit one event per question.
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* answer_kind: 'option' (exact label match), 'custom' (free-text), 'no_answer' (missing/empty).
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*/
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/** Collect concatenated text from all assistant text blocks in the turn. */
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function assistantTextOfTurn(turn) {
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const parts = [];
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for (const e of turn || []) {
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if (!e || !e.message || e.message.role !== 'assistant') continue;
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const content = Array.isArray(e.message.content) ? e.message.content : [];
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for (const b of content) {
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if (b && b.type === 'text' && typeof b.text === 'string') parts.push(b.text);
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}
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}
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return parts.join('\n');
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}
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const TRIGGER_PATTERNS = [
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/\bPravila\s+§\d+(?:\.\d+)?/g,
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/\bADR-\d+/g,
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/\bPSR_v1\s+R\d+(?:\.\d+)?/g,
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/\brouting-off-phase\s+L\d+/g,
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/\bL\d+\s+chain/g,
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/\bhard-(?:floor|rule)\b/gi,
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];
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/** Heuristic triggers from assistant text. Conservative-broad — false positives OK. */
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export function extractTriggers(turn) {
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const text = assistantTextOfTurn(turn);
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const out = new Set();
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for (const re of TRIGGER_PATTERNS) {
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const matches = text.match(re);
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if (matches) for (const m of matches) {
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const norm = /^L\d+\s+chain$/.test(m) ? `routing-off-phase ${m.split(/\s+/)[0]}` : m;
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out.add(norm);
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}
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}
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return [...out];
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}
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const CANDIDATE_NUMBERED_RE = /^\s*\d+[.\)]\s+([^\n]+)$/gm;
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const CANDIDATE_BULLET_RE = /^\s*[-*]\s+([^\n]+)$/gm;
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/** Heuristic candidates: ≥2 numbered (preferred) or bulleted items. */
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export function extractCandidates(turn) {
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const text = assistantTextOfTurn(turn);
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const numbered = [...text.matchAll(CANDIDATE_NUMBERED_RE)].map((m) => m[1].trim());
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if (numbered.length >= 2) return numbered;
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const bulleted = [...text.matchAll(CANDIDATE_BULLET_RE)].map((m) => m[1].trim());
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if (bulleted.length >= 2) return bulleted;
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return [];
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}
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const BOUNDARY_PATTERNS = [
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/\bADR-\d+(?:\s+§\d+(?:\.\d+)?)?/g,
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/\bPSR_v1\s+R\d+(?:\.\d+)?/g,
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/\bPravila\s+§\d+(?:\.\d+)?/g,
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/\brouting-off-phase\s+L\d+/g,
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/\bL\d+\s+chain/g,
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];
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/** Heuristic boundaries — overlaps with triggers, dedup per-array only. */
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export function extractBoundaries(turn) {
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const text = assistantTextOfTurn(turn);
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const out = new Set();
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for (const re of BOUNDARY_PATTERNS) {
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const matches = text.match(re);
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if (matches) for (const m of matches) {
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const norm = /^L\d+\s+chain$/.test(m) ? `routing-off-phase ${m.split(/\s+/)[0]}` : m;
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out.add(norm);
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}
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}
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return [...out];
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}
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export function extractAskUserQuestionEvents(turn) {
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const events = [];
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for (const e of turn || []) {
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const tur = e && e.toolUseResult;
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if (!tur || !Array.isArray(tur.questions) || !tur.answers) continue;
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const qCount = tur.questions.length;
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for (const q of tur.questions) {
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const labels = (q.options || []).map((o) => o && o.label).filter((l) => typeof l === 'string');
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const answer = tur.answers[q.question];
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let answer_kind;
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if (typeof answer !== 'string' || answer.length === 0) answer_kind = 'no_answer';
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else if (labels.some((l) => l.trim() === answer.trim())) answer_kind = 'option';
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else answer_kind = 'custom';
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events.push({ kind: 'ask_user_question', question_count: qCount, answer_kind });
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}
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}
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return events;
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}
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/** Classify the opening user-prompt sentiment (per spec §6 / gap-resolution 1). */
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export function classifyPromptSignal(text) {
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const t = String(text || '').toLowerCase().trim();
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if (
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/не совсем|другое|другая|не сходится|wrong direction|не то\b|не так\b|переделай|отбой|\bстоп\b|почему ты|неверно|не верно|это не |не работает|не правильн|сломал|опять|снова не|всё ещё|все ещё|все еще|верни как|откат|\brevert\b|\bundo\b|still not|doesn'?t work|does not work|\bwrong\b/.test(
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t
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)
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) {
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return 'correction';
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}
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if (/^(ок|окей|ok|спасибо|супер|отлично|готово|дальше|идеально|класс|хорошо|принято|well done|\bnice\b)([,\s]|$)/.test(t)) {
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return 'approval';
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}
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if (/^(?:теперь|далее|следующее)(?=\s|[,.!?:;]|$)|^next\b|^now\b/.test(t)) return 'new_task';
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if (classifyTask(t) !== 'other' && t.length > 15) return 'new_task';
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return 'neutral';
|
|
}
|
|
|
|
const TIME_BURN_THRESHOLD_MS = 900000; // 15 min — turn wall-clock above this = time_burn
|
|
const PARSE_GAP_RATIO = 0.1; // >10% unparseable lines = parse_gap
|
|
|
|
/** Heuristic retry count: an errored tool whose name is used again later in the turn. */
|
|
function detectRetries(turn) {
|
|
const idToName = {};
|
|
const uses = [];
|
|
turn.forEach((entry, idx) => {
|
|
const content = entry && entry.message && Array.isArray(entry.message.content) ? entry.message.content : [];
|
|
for (const b of content) {
|
|
if (b && b.type === 'tool_use') {
|
|
idToName[b.id] = b.name;
|
|
uses.push({ name: b.name, idx });
|
|
}
|
|
}
|
|
});
|
|
const errors = [];
|
|
turn.forEach((entry, idx) => {
|
|
const content = entry && entry.message && Array.isArray(entry.message.content) ? entry.message.content : [];
|
|
for (const b of content) {
|
|
if (b && b.type === 'tool_result' && b.is_error === true) {
|
|
errors.push({ name: idToName[b.tool_use_id] || null, idx });
|
|
}
|
|
}
|
|
});
|
|
let retries = 0;
|
|
for (const err of errors) {
|
|
if (err.name && uses.some((u) => u.name === err.name && u.idx > err.idx)) retries += 1;
|
|
}
|
|
return retries;
|
|
}
|
|
|
|
/**
|
|
* Process events for the turn: hook_fired (summary), interrupt, retry,
|
|
* time_burn, parse_gap. broken/total/durationMs are computed by the caller.
|
|
*/
|
|
export function extractProcessEvents(turn, broken, total, durationMs) {
|
|
const events = [];
|
|
|
|
const hookCounts = {};
|
|
let hookErrors = 0;
|
|
for (const e of turn) {
|
|
const att = e && e.attachment;
|
|
if (att && (att.type === 'hook_success' || att.type === 'hook_error')) {
|
|
const name = att.hookName || 'unknown';
|
|
hookCounts[name] = (hookCounts[name] || 0) + 1;
|
|
if (att.type === 'hook_error') hookErrors += 1;
|
|
}
|
|
}
|
|
if (Object.keys(hookCounts).length > 0) {
|
|
events.push({ kind: 'hook_fired', counts: hookCounts, errors: hookErrors });
|
|
}
|
|
|
|
for (const e of turn) {
|
|
const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
|
|
const isUser = e && e.message && e.message.role === 'user';
|
|
if (
|
|
isUser &&
|
|
content.some((b) => b && b.type === 'text' && String(b.text || '').includes('[Request interrupted by user]'))
|
|
) {
|
|
events.push({ kind: 'interrupt' });
|
|
}
|
|
}
|
|
|
|
const retries = detectRetries(turn);
|
|
for (let i = 0; i < retries; i++) events.push({ kind: 'retry' });
|
|
|
|
if (durationMs > TIME_BURN_THRESHOLD_MS) {
|
|
events.push({ kind: 'time_burn', duration_ms: durationMs });
|
|
}
|
|
|
|
if (total > 0 && broken / total > PARSE_GAP_RATIO) {
|
|
events.push({ kind: 'parse_gap', broken, total });
|
|
}
|
|
|
|
// unrecovered_error: emitted iff the LAST tool_result in the turn was
|
|
// is_error=true. Distinguishes "turn ended on failure" from "errors that
|
|
// were retried away" (e.g., TDD red→green, expected-fail commands). The
|
|
// analyzer uses this event to flag `blocked` instead of raw error/retry
|
|
// count — see brain-retro-analyzer.inferOutcome (A-1 fix).
|
|
let lastToolResultIsError = null;
|
|
outer: for (let i = turn.length - 1; i >= 0; i--) {
|
|
const content =
|
|
turn[i] && turn[i].message && Array.isArray(turn[i].message.content) ? turn[i].message.content : [];
|
|
for (let j = content.length - 1; j >= 0; j--) {
|
|
const b = content[j];
|
|
if (b && b.type === 'tool_result') {
|
|
lastToolResultIsError = b.is_error === true;
|
|
break outer;
|
|
}
|
|
}
|
|
}
|
|
if (lastToolResultIsError === true) {
|
|
events.push({ kind: 'unrecovered_error' });
|
|
}
|
|
|
|
return events;
|
|
}
|
|
|
|
const ROUTING_TAG_RE =
|
|
/<!--\s*routing:\s*provenance=([\w_]+)\s+node=(\S+)\s+counterfactual=(\S+)\s*-->/;
|
|
|
|
/** Find the routing tag Claude prints when a method was user-directed (spec §4.2). */
|
|
export function parseRoutingTag(turn) {
|
|
for (const e of turn) {
|
|
const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
|
|
for (const b of content) {
|
|
if (b && b.type === 'text' && typeof b.text === 'string') {
|
|
const m = b.text.match(ROUTING_TAG_RE);
|
|
if (m) return { kind: m[1], node: m[2], claude_would_have_chosen: m[3] };
|
|
}
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
const REASONING_TAG_RE =
|
|
/<!--\s*reasoning:\s*triggers="([^"]*)"\s+candidates="([^"]*)"\s+boundaries="([^"]*)"\s*-->/;
|
|
|
|
/**
|
|
* Opt-in reasoning tag (Task 11). Claude may emit at most one such comment
|
|
* per turn to declare triggers / candidates / boundaries explicitly. Values
|
|
* are semicolon-separated. When present, parser merges them into the
|
|
* heuristic-derived arrays via Set-dedupe.
|
|
*/
|
|
export function parseReasoningTag(turn) {
|
|
for (const e of turn || []) {
|
|
const content = e && e.message && Array.isArray(e.message.content) ? e.message.content : [];
|
|
for (const b of content) {
|
|
if (b && b.type === 'text' && typeof b.text === 'string') {
|
|
const m = b.text.match(REASONING_TAG_RE);
|
|
if (m) {
|
|
const split = (s) => s.split(';').map((x) => x.trim()).filter(Boolean);
|
|
return { triggers: split(m[1]), candidates: split(m[2]), boundaries: split(m[3]) };
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/** Text of the last real user prompt — used by the Stop-hook routing-gate (Task 5). */
|
|
export function extractLastUserPromptText(transcriptText) {
|
|
const { entries } = parseLines(transcriptText);
|
|
const start = findTurnStart(entries);
|
|
return promptText(entries[start]);
|
|
}
|
|
|
|
/**
|
|
* Content of the last assistant message strictly before the turn start —
|
|
* the message that may have offered options to the user (spec §11.5).
|
|
*/
|
|
function extractLastAssistantContent(entries, turnStartIdx) {
|
|
for (let i = turnStartIdx - 1; i >= 0; i--) {
|
|
const e = entries[i];
|
|
if (e && e.message && e.message.role === 'assistant') {
|
|
const content = e.message.content;
|
|
if (Array.isArray(content)) return content;
|
|
if (typeof content === 'string') return content;
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/**
|
|
* Parse a transcript JSONL string into an observer episode (schema v2).
|
|
* @param {string} transcriptText - Raw JSONL transcript contents.
|
|
* @param {string|null} fallbackSessionId - Used when the transcript has no sessionId.
|
|
* @returns {object} v2 episode.
|
|
*/
|
|
export function parseTranscript(transcriptText, fallbackSessionId = null) {
|
|
const { entries, broken, total } = parseLines(transcriptText);
|
|
|
|
const withSession = entries.find((e) => e && e.sessionId);
|
|
const sessionId =
|
|
(withSession && withSession.sessionId) || fallbackSessionId || `unknown-${Date.now()}`;
|
|
|
|
const start = findTurnStart(entries);
|
|
const turn = entries.slice(start);
|
|
|
|
const stamps = turn.map((e) => e && e.timestamp).filter(Boolean);
|
|
const started_at = stamps[0] || new Date().toISOString();
|
|
const ended_at = stamps[stamps.length - 1] || started_at;
|
|
const durationMs = new Date(ended_at) - new Date(started_at);
|
|
|
|
const { skills, counts, errors } = collectToolUse(turn);
|
|
|
|
const events = [];
|
|
for (const skill of skills) events.push({ kind: 'skill_invoked', skill });
|
|
if (Object.keys(counts).length > 0) events.push({ kind: 'tool_summary', counts });
|
|
for (const err of errors) {
|
|
events.push({ kind: 'error', tool: err.tool, summary: err.summary });
|
|
}
|
|
events.push(...extractProcessEvents(turn, broken, total, durationMs));
|
|
events.push(...extractAskUserQuestionEvents(turn));
|
|
|
|
const usedSuperpowers = skills.some((s) => String(s).startsWith(SUPERPOWERS_PREFIX));
|
|
const prompt = promptText(entries[start]);
|
|
|
|
const lastAsstContent = extractLastAssistantContent(entries, start);
|
|
const choice = detectChoiceProvenance(prompt, lastAsstContent) || detectAskUserQuestionChoice(turn);
|
|
let decision_provenance;
|
|
if (choice) {
|
|
decision_provenance = choice;
|
|
} else {
|
|
const tag = parseRoutingTag(turn);
|
|
decision_provenance =
|
|
tag && tag.kind === 'user_directed_method'
|
|
? { kind: 'user_directed_method', claude_would_have_chosen: tag.claude_would_have_chosen }
|
|
: { kind: 'autonomous', claude_would_have_chosen: null };
|
|
}
|
|
|
|
return {
|
|
schema_version: 2,
|
|
task_id: sessionId,
|
|
task_ref: sessionId,
|
|
timestamps: { started_at, ended_at },
|
|
path_type: usedSuperpowers ? 'regulated' : 'improvised',
|
|
outcome: 'unknown',
|
|
prompt_signal: classifyPromptSignal(prompt),
|
|
decision_provenance,
|
|
environment: extractEnvironment(entries, start),
|
|
task_size: extractTaskSize(turn),
|
|
task_cost: extractTokenUsage(turn),
|
|
primary_rationale: (() => {
|
|
const tag = parseReasoningTag(turn);
|
|
const merge = (heur, fromTag) => [...new Set([...heur, ...fromTag])];
|
|
return {
|
|
step: 1,
|
|
node_chosen: skills.length > 0 ? skills[0] : 'direct',
|
|
triggers_matched: merge(extractTriggers(turn), tag ? tag.triggers : []),
|
|
candidates_considered: merge(extractCandidates(turn), tag ? tag.candidates : []),
|
|
boundaries_applied: merge(extractBoundaries(turn), tag ? tag.boundaries : []),
|
|
hard_floor: usedSuperpowers
|
|
? { invoked: true, rules: ['Pravila §12'] }
|
|
: { invoked: false, rules: [] },
|
|
task_classification: classifyTask(prompt),
|
|
};
|
|
})(),
|
|
events,
|
|
};
|
|
}
|