Files
portal/tools/brain-retro-analyzer.mjs
T
Дмитрий a6f44e5bb4 feat(observer): brain-retro analyzer — outcome inference + factor matrix
Pure deterministic Layer-4 aggregation module (spec §6) for the /brain-retro
skill. Exports: dedupeEpisodes, inferOutcome, groupEpisodesToTasks,
findCausalChains, buildFactorMatrix, analyze. Read-only — never writes JSONL.
11/11 tests green. CLI smoke: 10 real episodes → valid JSON with all 5 keys.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 10:47:57 +03:00

176 lines
6.0 KiB
JavaScript

#!/usr/bin/env node
/**
* Brain-retro analyzer (brain governance, observer factor-analysis spec §6).
* Pure, deterministic Layer-4 aggregation over observer episodes for the
* /brain-retro skill. Read-only — never writes JSONL. No LLM.
*
* Security Guidance #40: pure parsing — no exec/execSync.
*/
import { readFileSync, existsSync } from 'fs';
const SIZE_SMALL = 20;
const SIZE_LARGE = 60;
/**
* Deduplicate the routing-gate double-write: a turn that was blocked then
* re-stopped yields two episodes with the same task_id + started_at. Keep the
* last (most complete). observer_error markers are all kept.
*/
export function dedupeEpisodes(episodes) {
const errors = episodes.filter((e) => e && e.observer_error);
const normal = episodes.filter((e) => e && !e.observer_error);
const byKey = new Map();
for (const e of normal) {
byKey.set(`${e.task_id}|${(e.timestamps || {}).started_at}`, e);
}
return [...byKey.values(), ...errors];
}
/** Infer the true outcome of an episode from the next episode's opening prompt. */
export function inferOutcome(episode, nextEpisode) {
if (episode && Array.isArray(episode.events) && episode.events.some((e) => e.kind === 'interrupt')) {
return 'partial';
}
if (!nextEpisode) return 'unknown';
if (nextEpisode.prompt_signal === 'correction') return 'rework';
if (nextEpisode.prompt_signal === 'approval' || nextEpisode.prompt_signal === 'new_task') return 'success';
return 'unknown';
}
function bySessionSorted(episodes) {
const map = new Map();
for (const e of episodes) {
if (e.observer_error) continue;
const sid = e.task_id || 'unknown';
if (!map.has(sid)) map.set(sid, []);
map.get(sid).push(e);
}
for (const eps of map.values()) {
eps.sort((a, b) =>
String((a.timestamps || {}).started_at).localeCompare(String((b.timestamps || {}).started_at))
);
}
return map;
}
/** Group episodes into tasks: a new task starts after a success or on a new_task prompt. */
export function groupEpisodesToTasks(episodes) {
const tasks = [];
for (const [sid, eps] of bySessionSorted(episodes)) {
let current = null;
eps.forEach((episode, i) => {
const prev = eps[i - 1];
const prevOutcome = prev ? inferOutcome(prev, episode) : null;
const isNewTask = i === 0 || prevOutcome === 'success' || episode.prompt_signal === 'new_task';
if (isNewTask) {
current = { task_ref: `${sid}#${tasks.length + 1}`, episodes: [] };
tasks.push(current);
}
current.episodes.push(episode);
});
}
return tasks;
}
/** Causal-chain candidates: an errored episode → a later episode sharing a file. */
export function findCausalChains(episodes) {
const sorted = episodes
.filter((e) => !e.observer_error)
.slice()
.sort((a, b) =>
String((a.timestamps || {}).started_at).localeCompare(String((b.timestamps || {}).started_at))
);
const chains = [];
for (let i = 0; i < sorted.length - 1; i++) {
const a = sorted[i];
const hasError = Array.isArray(a.events) && a.events.some((e) => e.kind === 'error');
if (!hasError) continue;
const filesA = new Set(((a.task_size || {}).files) || []);
if (filesA.size === 0) continue;
for (let j = i + 1; j < sorted.length; j++) {
const b = sorted[j];
const shared = (((b.task_size || {}).files) || []).filter((f) => filesA.has(f));
if (shared.length > 0) {
chains.push({
from: `${a.task_id}|${(a.timestamps || {}).started_at}`,
to: `${b.task_id}|${(b.timestamps || {}).started_at}`,
sharedFiles: shared,
});
break;
}
}
}
return chains;
}
function sizeBucket(toolCalls) {
const n = Number(toolCalls) || 0;
return n < SIZE_SMALL ? 'small' : n <= SIZE_LARGE ? 'medium' : 'large';
}
const FACTOR_FNS = {
decision_provenance: (e) => (e.decision_provenance || {}).kind || 'unknown',
economy_level: (e) => String((e.environment || {}).economy_level ?? 'null'),
model: (e) => (e.environment || {}).model || 'null',
post_compaction: (e) => String((e.environment || {}).post_compaction ?? false),
task_size: (e) => sizeBucket((e.task_size || {}).tool_calls),
node_chosen: (e) => (e.primary_rationale || {}).node_chosen || 'direct',
task_classification: (e) => (e.primary_rationale || {}).task_classification || 'other',
};
/** Factor matrix: rows = factor values, columns = outcome distribution (spec §6). */
export function buildFactorMatrix(episodesWithOutcome) {
const matrix = {};
for (const [fname, fn] of Object.entries(FACTOR_FNS)) {
matrix[fname] = {};
for (const e of episodesWithOutcome) {
const val = fn(e);
const outcome = e._inferredOutcome || 'unknown';
matrix[fname][val] = matrix[fname][val] || {};
matrix[fname][val][outcome] = (matrix[fname][val][outcome] || 0) + 1;
}
}
return matrix;
}
/** Full deterministic aggregation: dedup → infer outcomes → group → chains → matrix. */
export function analyze(episodes) {
const deduped = dedupeEpisodes(episodes);
const normal = deduped.filter((e) => !e.observer_error);
for (const eps of bySessionSorted(normal).values()) {
eps.forEach((episode, i) => {
episode._inferredOutcome = inferOutcome(episode, eps[i + 1]);
});
}
return {
episodeCount: normal.length,
observerErrorCount: deduped.length - normal.length,
tasks: groupEpisodesToTasks(normal),
causalChains: findCausalChains(normal),
factorMatrix: buildFactorMatrix(normal),
};
}
function loadEpisodes(files) {
const eps = [];
for (const f of files) {
if (!existsSync(f)) continue;
for (const line of readFileSync(f, 'utf-8').split('\n')) {
const t = line.trim();
if (!t) continue;
try {
eps.push(JSON.parse(t));
} catch {
// skip broken line
}
}
}
return eps;
}
if (process.argv[1] && process.argv[1].replace(/\\/g, '/').endsWith('/brain-retro-analyzer.mjs')) {
const result = analyze(loadEpisodes(process.argv.slice(2)));
console.log(JSON.stringify(result, null, 2));
process.exit(0);
}