mirror of
https://github.com/lukaszraczylo/claude-adam.git
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440fb52eb1
Implements 7 improvements grounded in MOSS paper (arXiv 2605.22794): 1. Transcript capture (§3.4): context_ring buffer in adam-observe.mjs captures last 8 events around struggle signals as context_window. 2. Evidence batching (§3.1): new adam-batch.mjs pre-clusters windowed journal entries into coherent failure batches by (signal_type, cluster_key). 3. Multi-stage analysis (§3.3): SKILL.md dispatches adam agent in two stages (diagnose+plan → implement) with inter-stage validation gate. 4. Pre-apply verification (§3.4): 4-check deterministic gate before auto-apply (source entries exist, diagnosis grounded, type-evidence match, no conflicting recent proposals). 5. Auto-rollback (§3.5): new adam-rollback.mjs reverts regressed proposals detected by A/B measurement, creates regression nudges. 6. Harness self-modification (§1 Table 1): new harness_edit proposal type targeting adam's own scripts with stricter gates (confidence≥5, never auto-apply, test-suite-gated). 7. Keypoint matrix evaluation (§4.2): 5 capability dimensions (tool_selection, scope_discipline, error_recovery, first_attempt, build_reliability) scored per batch for structured evaluation. Test suite: 94 → 114 tests (20 new), all passing.
185 lines
6.2 KiB
JavaScript
Executable File
185 lines
6.2 KiB
JavaScript
Executable File
#!/usr/bin/env node
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// adam-batch.mjs — pre-clusters windowed journal entries into coherent failure
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// batches before analyst dispatch. Implements MOSS §3.1: "anchored to an
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// automatically curated batch of production-failure evidence."
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//
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// Each batch groups entries by (signal_type, cluster_key) where cluster_key
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// follows the same clustering rules as agents/adam.md §4:
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// correction → tokenized phrase (cross-cwd)
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// retry_loop → tool
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// weak_agent → subagent_type
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// tool_error_loop→ fp
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// dead_end → session
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// edit_churn → file basename
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// build_loop → session
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// subagent_dispatch_pattern → subagent_type
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// silent_drift → active_skills[0]
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// error_after_recovery → (recovered_from, original_fp)
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// correction_free_streak → active_skills[0]
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// clean_recovery → (recovered_from, active_skills[0])
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// task_completed → sorted tool_kinds tuple
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//
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// CLI:
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// adam-batch.mjs [--input <jsonl-path>] [--min-entries N] [--min-sessions N]
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//
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// Output: JSON object with `batches` array and `unbatched` count.
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import { readFileSync } from "node:fs";
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import { readJsonlSafe } from "./adam-utils.mjs";
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const DEFAULT_MIN_ENTRIES = 1;
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const DEFAULT_MIN_SESSIONS = 1;
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const CORRECTION_STOPWORDS = new Set([
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"the", "a", "an", "and", "or", "but", "of", "to", "for", "in", "on",
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"with", "use", "when", "where", "what", "why", "how", "this", "that",
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"these", "those", "is", "are", "was", "were", "be", "been", "being",
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"do", "does", "did", "doing", "has", "have", "had", "your", "you",
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"i", "it", "as", "at", "by", "from", "not", "no",
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]);
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function tokenizePhrase(phrase) {
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if (!phrase || typeof phrase !== "string") return "";
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return phrase.toLowerCase()
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.split(/\s+/)
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.map(t => t.replace(/^[^\w']+|[^\w']+$/g, ""))
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.filter(t => t && !CORRECTION_STOPWORDS.has(t))
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.sort()
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.join("|");
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}
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function clusterKey(entry) {
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if (!entry || typeof entry !== "object") return null;
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const t = entry.type;
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switch (t) {
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case "correction":
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return tokenizePhrase(entry.phrase) || "unknown";
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case "retry_loop":
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return entry.tool || "unknown";
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case "weak_agent":
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case "subagent_dispatch_pattern":
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return entry.subagent_type || "unknown";
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case "tool_error_loop":
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return entry.fp || "unknown";
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case "dead_end":
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case "build_loop":
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return entry.session || "unknown";
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case "edit_churn":
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return entry.file ? entry.file.split("/").pop() : "unknown";
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case "silent_drift":
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case "correction_free_streak":
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return Array.isArray(entry.active_skills) ? (entry.active_skills[0] || "") : "";
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case "error_after_recovery":
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return `${entry.recovered_from || "?"}:${entry.original_fp || "?"}`;
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case "clean_recovery":
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return `${entry.recovered_from || "?"}:${Array.isArray(entry.active_skills) ? (entry.active_skills[0] || "") : ""}`;
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case "task_completed":
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return Array.isArray(entry.tool_kinds) ? entry.tool_kinds.slice().sort().join(",") : "unknown";
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default:
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return entry.session || "unknown";
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}
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}
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function parseArgs(argv) {
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const args = { input: null, minEntries: DEFAULT_MIN_ENTRIES, minSessions: DEFAULT_MIN_SESSIONS, help: false };
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for (let i = 0; i < argv.length; i++) {
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const a = argv[i];
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if (a === "--input" && i + 1 < argv.length) args.input = argv[++i];
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else if (a === "--min-entries" && i + 1 < argv.length) {
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const n = Number(argv[++i]);
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if (!Number.isNaN(n) && n > 0) args.minEntries = n;
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}
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else if (a === "--min-sessions" && i + 1 < argv.length) {
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const n = Number(argv[++i]);
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if (!Number.isNaN(n) && n > 0) args.minSessions = n;
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}
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else if (a === "--help" || a === "-h") args.help = true;
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}
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return args;
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}
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export function buildBatches(entries, opts = {}) {
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const minEntries = opts.minEntries || DEFAULT_MIN_ENTRIES;
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const minSessions = opts.minSessions || DEFAULT_MIN_SESSIONS;
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const map = new Map();
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for (const e of entries || []) {
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if (!e || typeof e !== "object" || !e.type) continue;
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const key = `${e.type}::${clusterKey(e)}`;
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if (!map.has(key)) {
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map.set(key, {
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batch_id: null,
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signal_type: e.type,
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cluster_key: clusterKey(e),
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entries: [],
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sessions: new Set(),
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cwds: new Set(),
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});
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}
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const batch = map.get(key);
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batch.entries.push(e);
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if (e.session) batch.sessions.add(e.session);
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if (e.cwd) batch.cwds.add(e.cwd);
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}
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const batches = [];
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let unbatched = 0;
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let id = 1;
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for (const [, batch] of map) {
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if (batch.entries.length < minEntries || batch.sessions.size < minSessions) {
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unbatched += batch.entries.length;
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continue;
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}
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batch.batch_id = `b${id++}`;
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batches.push({
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batch_id: batch.batch_id,
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signal_type: batch.signal_type,
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cluster_key: batch.cluster_key,
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entry_count: batch.entries.length,
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session_count: batch.sessions.size,
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cwd_count: batch.cwds.size,
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has_context_window: batch.entries.some(e => Array.isArray(e.context_window) && e.context_window.length > 0),
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entries: batch.entries,
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});
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}
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batches.sort((a, b) => b.entry_count - a.entry_count);
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return { batches, unbatched, total: (entries || []).length };
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}
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function main() {
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const args = parseArgs(process.argv.slice(2));
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if (args.help) {
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process.stdout.write("usage: adam-batch.mjs [--input <jsonl-path>] [--min-entries N] [--min-sessions N]\n");
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process.exit(0);
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}
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try {
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let entries;
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if (args.input) {
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entries = readJsonlSafe(args.input);
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} else if (!process.stdin.isTTY) {
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const buf = readFileSync(0, "utf8");
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entries = [];
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for (const line of buf.split("\n")) {
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if (!line) continue;
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try { entries.push(JSON.parse(line)); } catch { /* skip */ }
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}
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} else {
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process.stderr.write("adam-batch: no input (use --input or pipe)\n");
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process.exit(1);
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}
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const result = buildBatches(entries, { minEntries: args.minEntries, minSessions: args.minSessions });
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process.stdout.write(JSON.stringify(result) + "\n");
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process.exit(0);
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} catch (e) {
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process.stderr.write(`adam-batch error: ${e.message}\n`);
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process.exit(1);
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}
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}
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if (import.meta.url === `file://${process.argv[1]}`) {
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main();
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}
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export { clusterKey, tokenizePhrase };
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