3 Commits

Include renames

Author	SHA1	Message	Date
3 people	e5a9f0126a	feat: GStackBrain — 16 new skills, resolver, conventions, identity layer (v0.10.0) (#120) ... * feat: migrate 8 existing skills to conformance format Add YAML frontmatter (name, version, description, triggers, tools, mutating), Contract, Anti-Patterns, and Output Format sections to all existing skills. Rename Workflow to Phases. Ingest becomes thin router delegating to specialized ingestion skills (Phase 2). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add RESOLVER.md, conventions directory, and output rules RESOLVER.md is the skill dispatcher modeled on Wintermute's AGENTS.md. Categorized routing table: Always-on, Brain ops, Ingestion, Thinking, Operational, Setup, Identity. Conventions directory extracts cross-cutting rules (quality, brain-first lookup, model routing, test-before-bulk). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add skills conformance and resolver validation tests skills-conformance.test.ts validates every skill has YAML frontmatter with required fields, Contract, Anti-Patterns, and Output Format sections, and manifest.json coverage. resolver.test.ts validates routing table categories, skill path existence, and manifest-to-resolver coverage. 50 new tests. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 9 brain skills from Wintermute (Phase 2) Generalized from Wintermute's battle-tested skills: - signal-detector: always-on idea+entity capture on every message - brain-ops: brain-first lookup, read-enrich-write loop, source attribution - idea-ingest: links/articles/tweets with author people page mandatory - media-ingest: video/audio/PDF/book with entity extraction (absorbs video/youtube/book) - meeting-ingestion: transcripts with attendee enrichment chaining - citation-fixer: audit and fix citation formatting - repo-architecture: filing rules by primary subject - skill-creator: create skills with conformance standard + MECE check - daily-task-manager: task lifecycle with priority levels All Garry-specific references generalized. Core workflows preserved. Updated RESOLVER.md and manifest.json. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add operational infrastructure + identity layer (Phase 3) Operational skills: - daily-task-prep: morning prep with calendar context and open threads - cross-modal-review: quality gate via second model with refusal routing - cron-scheduler: schedule staggering, quiet hours, wake-up override, idempotency - reports: timestamped reports with keyword routing - testing: skill validation framework (conformance checks) - soul-audit: 6-phase interview generating SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md - webhook-transforms: external events to brain signals with dead-letter queue Identity layer: - SOUL.md template (agent identity, generated by soul-audit) - USER.md template (user profile, generated by soul-audit) - ACCESS_POLICY.md template (4-tier access control) - HEARTBEAT.md template (operational cadence) - cross-modal.yaml convention (review pairs, refusal routing chain) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update CLAUDE.md with 24 skills, RESOLVER.md, conventions, templates GBrain is now a GStack mod for agent platforms. Updated architecture description, key files listing (16 new skill files, RESOLVER.md, conventions, templates), skills section (24 skills organized by resolver categories), and testing section (new conformance and resolver tests). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add GStack detection + mod status to gbrain init (Phase 4) After brain initialization, gbrain init now reports: - Number of skills loaded (from manifest.json) - GStack detection (checks known host paths, uses gstack-global-discover if available) - GStack install instructions if not found - Resolver and soul-audit pointers Also adds installDefaultTemplates() for SOUL.md/USER.md/ACCESS_POLICY.md/HEARTBEAT.md deployment, and detectGStack() using gstack-global-discover with fallback to known paths (DRY: doesn't reimplement GStack's host detection logic). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: v0.10.0 release documentation - CHANGELOG: 24 skills, signal detector, RESOLVER.md, soul-audit, access control, conventions, conformance standard, GStack detection in init - README: updated skill section with 24 skills, resolver, conventions - TODOS: added runtime MCP access control (P1) - VERSION: 0.9.2 → 0.10.0 - package.json + manifest.json version bumped Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add skill table to CHANGELOG v0.10.0 16-row table detailing every new skill, what it does, and why it matters. Written to sell the upgrade, not document the implementation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: restore package.json version after merge conflict resolution Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: zero-based README rewrite for GStackBrain v0.10.0 Lead with GStack mod identity. 24 skills table organized by category. Install block references RESOLVER.md and soul-audit. GBrain+GStack relationship explained. Removed redundancy (733 -> 406 lines). All essential content preserved: install, recipes, architecture, search, commands, engines, voice, knowledge model. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: extract install block to INSTALL_FOR_AGENTS.md, simplify README The 30-line copy-paste install block becomes one line: "Retrieve and follow INSTALL_FOR_AGENTS.md" Benefits: agent always gets latest instructions (no stale copy-paste), README stays clean, install details live where agents read them. README now leads with what GBrain does ("gives your agent a brain") instead of GStack relationship. Removed "requires frontier model" note. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 3 bugs in init.ts from merge conflict resolution 1. llstatSync typo (merge corruption) → lstatSync 2. __dirname undefined in ESM module → fileURLToPath polyfill 3. require('fs') in ESM → use imported readFileSync All three would crash gbrain init at runtime. Caught by /review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add checkResolvable shared core function for resolver validation Shared function at src/core/check-resolvable.ts validates that all skills are reachable from RESOLVER.md, detects MECE overlaps (with whitelist for always-on/router skills), finds gaps in frontmatter triggers, and scans for DRY violations. Returns structured ResolvableIssue objects with machine-parseable fix objects alongside human-readable action strings. Three call sites: bun test, gbrain doctor, skill-creator skill. Cleans up test/resolver.test.ts: removes stale 9-line skip list, imports from production check-resolvable.ts instead of reimplementing parsing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: expand doctor with resolver validation, filesystem-first architecture Doctor now runs filesystem checks (resolver health, skill conformance) before connecting to DB. New --fast flag skips DB checks. Falls back to filesystem-only when DB is unavailable. Adds schema_version: 2 to JSON output, composite health score (0-100), and structured issues array with action strings for agent parsing. Resolver health check calls checkResolvable() and surfaces actionable fix instructions. Link integrity check uses engine.getHealth() dead_links count. CLI routing split: doctor dispatched before connectEngine() so filesystem checks always run. Fixes Codex-identified blocker where doctor required DB. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add adaptive load-aware throttling and fail-improve loop backoff.ts: System load checking (CPU via os.loadavg, memory via os.freemem), exponential backoff with 20-attempt max guard, active hours multiplier (2x slower during waking hours), concurrent process limit (max 2). Windows-safe: defaults to "proceed" when os.loadavg returns zeros. fail-improve.ts: Deterministic-first, LLM-fallback pattern with JSONL failure logging. Cascade failure handling: when both paths fail, throws LLM error and logs both. Log rotation at 1000 entries. Call count tracking for deterministic hit rate metrics. Auto-generates test cases from successful LLM fallbacks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add transcription service and enrichment-as-a-service transcription.ts: Groq Whisper (default) with OpenAI fallback. Files >25MB segmented via ffmpeg. Provider auto-detection from env vars. Clear error messages for missing API keys and unsupported formats. enrichment-service.ts: Global enrichment service callable from any ingest pathway. Entity slug generation (people/jane-doe, companies/acme-corp), mention counting via searchKeyword, tier auto-escalation (Tier 3→2→1 based on mention frequency and source diversity), batch enrichment with backoff throttling, regex-based entity extraction from text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add data-research skill with recipe system, extraction, dedup, tracker New skill: data-research — one parameterized pipeline for any email-to- structured-data workflow (investor updates, donations, company metrics). 7-phase pipeline: define recipe, search, classify, extract (with extraction integrity rule), archive, deduplicate, update tracker. data-research.ts: Recipe validation, MRR/ARR/runway/headcount regex extraction (battle-tested patterns), dedup with configurable tolerance, markdown tracker parsing/appending, quarterly/monthly date windowing, 6-phase HTML email stripping with 500KB ReDoS cap. Registers data-research in manifest.json (25th skill) and RESOLVER.md. Fixes backoff test robustness for high-load systems. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.10.0 infrastructure additions CLAUDE.md: added 6 new core files (check-resolvable, backoff, fail-improve, transcription, enrichment-service, data-research), 6 new test files, updated skill count to 25, test file count to 34. README.md: updated skill count to 25, added data-research to skills table. CHANGELOG.md: added Infrastructure section documenting resolver validation, doctor expansion, adaptive throttling, fail-improve loop, voice transcription, enrichment service, and data-research skill. TODOS.md: anonymized personal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: doctor.ts use ES module imports, harden backoff test Replace require('fs') with ES module import in doctor.ts for consistency with the rest of the file. Backoff test made resilient to parallel test execution leaking module-level state. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README rewrite with production brain stats, sample output, new infrastructure Lead with the flex: 17,888 pages, 4,383 people, 723 companies, 526 meeting transcripts built in 12 days. Show sample query output so readers see what they'll get. Document self-improving infrastructure (tier auto-escalation, fail-improve loop, doctor trajectory). Add data-research recipes to Getting Data In. Update commands section with doctor --fix, transcribe, research init/list. Fix stale "24" references to "25". Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with YC President origin and production agent deployments Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with skill philosophy and link to Thin Harness Fat Skills Skills section now explains: skill files are code, they encode entire workflows, they call deterministic TypeScript for the parts that shouldn't be LLM judgment. Links to the tweet and the architecture essay. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: link GStack repo, add 70K stars and 30K daily users Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: remove meeting transcript count from README (sensitive) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with YC President origin and production agent deployments Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: rename political-donations recipe to expense-tracker (sensitivity) Renamed the built-in data-research recipe from political-donations to expense-tracker across README, CHANGELOG, SKILL.md, and reports routing. Same extraction patterns (amounts, dates, recipients), neutral framing. Also renamed social-radar keyword route to social-mentions. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-14 19:41:34 -10:00
3 people	a86f995883	feat: GBrain v0.3.0 — contract-first architecture + ClawHub plugin (#7) ... * feat: contract-first operations.ts with OperationError, dry_run, importFromContent 30 shared operations as single source of truth for CLI and MCP. - OperationError with typed error codes (page_not_found, invalid_params, etc.) - dry_run support on all mutating operations - importFromContent split from importFile with transaction wrapping - Idempotency hash now includes ALL fields (title, type, frontmatter, tags) - Config env var fallback: GBRAIN_DATABASE_URL > DATABASE_URL > config file Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: rewrite MCP server + CLI + tools-json from operations server.ts: 233 -> ~80 lines. Tool definitions and dispatch generated from operations[]. cli.ts: shared operations auto-registered, CLI-only commands kept as manual dispatch. tools-json: generated FROM operations[], eliminating the third contract surface. Parity test verifies structural contract between operations, CLI, and MCP. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: delete 12 command files migrated to operations.ts Handler logic for get, put, delete, list, search, query, health, stats, tags, link, timeline, and version now lives in operations.ts. Kept: init, upgrade, import, export, files, embed, sync, serve, call, config. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: init --non-interactive, upgrade verification, schema migration - gbrain init --non-interactive --url <url> for plugin mode (no TTY required) - Post-upgrade version verification in gbrain upgrade - Drop storage_url from files table (storage_path is the only identifier) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: tool-agnostic skills + new setup skill All 7 skills rewritten with intent-based language instead of CLI commands. Works with both CLI and MCP plugin contexts. New setup skill replaces install: auto-provision Supabase via CLI, AGENTS.md injection, target TTHW < 2 min. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: ClawHub bundle plugin, CI workflows, v0.3.0 - openclaw.plugin.json with configSchema, MCP server config, skill listing - GitHub Actions: test on push/PR, multi-platform release (macOS arm64 + Linux x64) - Version bump 0.3.0, CHANGELOG, README ClawHub section, CLAUDE.md updated Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: idempotency hash mismatch + MCP dry_run passthrough importFromContent now passes its all-fields hash through putPage via content_hash on PageInput, so the stored hash matches the computed hash. Previously the skip-if-unchanged check never fired because the hash formulas differed. MCP server now passes dry_run from tool params to OperationContext. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.3.0.0) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: schema loader handles PL/pgSQL $$ blocks Delete the semicolon-based SQL splitter in db.ts which broke on PL/pgSQL trigger functions containing semicolons inside $$ delimiter blocks. Use single conn.unsafe(schemaSql) call instead — the postgres driver handles multi-statement SQL natively. schema.sql already uses IF NOT EXISTS / CREATE OR REPLACE for idempotency. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: E2E test infrastructure + realistic brain fixtures Add test infrastructure for running E2E tests against real Postgres+pgvector. Includes: - test/e2e/helpers.ts: DB lifecycle, fixture import, timing, diagnostics - 13 fixture files as a miniature realistic brain (people, companies, deals, meetings, concepts, projects, sources) following the compiled truth + timeline format from GBRAIN_RECOMMENDED_SCHEMA.md - docker-compose.test.yml: local pgvector convenience (port 5433) - .env.testing.example: template for test credentials - package.json: add test:e2e script Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: E2E test suites + CI workflow Tier 1 (mechanical.test.ts): 14 test suites covering all operations against real Postgres — page CRUD, search with quality scoring, links, tags, timeline, versions, admin, chunks, resolution, ingest log, raw data, files, idempotency stress, setup journey (full CLI flow), init edge cases, schema idempotency, schema diff guard, performance baselines. Tier 1 (mcp.test.ts): MCP protocol test — spawns server, sends JSON-RPC, verifies tools/list matches operations count. Tier 2 (skills.test.ts): OpenClaw skill tests — ingest, query, health. Skips gracefully when dependencies missing. CI (.github/workflows/e2e.yml): Tier 1 on every PR (pgvector service), Tier 2 nightly/manual with API key secrets. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: E2E test fixes + traverseGraph jsonb cast - Fix traverseGraph query: cast json_agg to jsonb_agg so SELECT DISTINCT works - Fix put_page tests to use importFromContent with noEmbed (no OpenAI key in Tier 1) - Fix get_health assertion (page_count not total_pages) - Fix raw_data test to handle JSONB string/object return - Simplify MCP test to verify tool generation directly - Add timeouts to CLI subprocess tests - Use port 5434 for docker-compose (5433 often in use) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * docs: update all project docs for E2E test suite - CLAUDE.md: updated test count (9 unit + 3 E2E), added E2E test instructions, fixed skill count to 8 - CONTRIBUTING.md: updated project structure with test/e2e/, added E2E test instructions, rewrote "Adding a new command" to reflect contract-first architecture (add to operations.ts, done) - README.md: fixed table count (10 not 9), added recommended schema doc to Docs section, added E2E instructions to Contributing section - CHANGELOG.md: added E2E test suite, docker-compose, schema loader fix, and traverseGraph jsonb fix to v0.3.0 entry Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-08 23:26:11 -10:00
3 people	b22cbd349a	feat: GBrain v0.1.0 — Postgres-native personal knowledge brain (#1) ... * chore: add CLAUDE.md with project context and gstack skill routing rules Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: initialize project with Bun + TypeScript package.json with dependencies (postgres, pgvector, openai, anthropic, MCP SDK, gray-matter). TypeScript config targeting ESNext with bundler module resolution. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add foundation layer — engine interface, Postgres engine, schema BrainEngine pluggable interface with full PostgresEngine: CRUD, search (keyword + vector), links, tags, timeline, versions, stats, health, ingest log, config. Trigger-based tsvector spanning pages + timeline_entries. Markdown parser with frontmatter, compiled_truth / timeline splitting, and round-trip serialization. 19 tests passing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 3-tier chunking and embedding service Recursive delimiter-aware chunker (5-level hierarchy, 300-word chunks, 50-word overlap). Semantic chunker with Savitzky-Golay boundary detection and recursive fallback. LLM-guided chunker via Claude Haiku with sliding window topic detection. OpenAI embedding service with batch support, exponential backoff, and rate limit handling. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add hybrid search with RRF fusion, expansion, and 4-layer dedup Hybrid search merges vector (pgvector HNSW) + keyword (tsvector) via Reciprocal Rank Fusion. Multi-query expansion via Claude Haiku generates 2 alternative phrasings. 4-layer dedup pipeline: by source, cosine similarity, type diversity (60% cap), per-page cap. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add GBRAIN_V0 spec, pluggable engine architecture, SQLite engine plan GBRAIN_V0.md: full product spec with architecture decisions, CLI commands, schema, search architecture, chunking strategies, first-time experience, and future plans. ENGINES.md: pluggable engine interface, capability matrix, how to add new backends. SQLITE_ENGINE.md: complete SQLite implementation plan with schema, FTS5 setup, vector search options, and contributor guide. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add CLI with all commands Full CLI dispatcher with 25+ commands: init (Supabase wizard), get, put, delete, list, search, query (hybrid RRF), import (bulk with progress bar), export (round-trip), embed, stats, health, tag/untag/tags, link/unlink/ backlinks/graph, timeline/timeline-add, history/revert, config, upgrade, serve, call. Smart slug resolution on reads. Version snapshots on updates. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add MCP stdio server with all brain tools 20 MCP tools mirroring CLI operations: get/put/delete/list pages, search (keyword), query (hybrid RRF + expansion), tags, links with graph traversal, timeline, stats, health, version history, and revert. Auto-chunks and embeds on put_page. CLI and MCP share the same engine. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 6 skill files and ClawHub manifest Fat markdown skills for AI agents: ingest (meetings/docs/articles with timeline merge), query (3-layer search + synthesis + citations), maintain (health checks, stale detection, orphan audit), enrich (external API enrichment), briefing (daily briefing compilation), migrate (universal migration from Obsidian/Notion/Logseq/markdown/CSV/JSON/Roam). ClawHub manifest for skill distribution. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add README, CONTRIBUTING, update CLAUDE.md test references README with quickstart, commands, architecture, library usage, MCP setup, and links to design docs. CONTRIBUTING with setup, project structure, and guides for adding commands and engines. CLAUDE.md updated to reference actual test files instead of planned-but-unwritten import test. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address adversarial review findings — 5 critical/high fixes - revertToVersion: add page_id check to prevent cross-page data corruption - traverseGraph: use UNION instead of UNION ALL for cycle safety - embedAll: preserve all chunks when embedding stale subset only - embedding: throw on retry exhaustion instead of returning zero vectors - putPage: validate slugs to prevent path traversal on export Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.1.0) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: expand README with schema, install, search architecture, and motivation Why it exists, how search works (with ASCII diagram), full database schema with all 9 tables and index details, chunking strategies explained, storage estimates, setup wizard walkthrough, knowledge model with example page, library usage with more examples, expanded skills table. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: add MIT license (Copyright 2026 Garry Tan) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add OpenClaw install flow as primary option in README OpenClaw users just say "install gbrain" and the orchestrator handles everything: package install, Supabase setup wizard, skill registration. Shows the conversational interface for querying, ingesting, and briefings. ClawHub and standalone CLI paths follow as alternatives. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add prerequisites and explicit OpenClaw install instructions Prerequisites table listing Supabase, OpenAI, and Anthropic dependencies with links. Environment variable setup. Explicit step-by-step prompt for OpenClaw users showing exactly what to tell the orchestrator. Note that search degrades gracefully without API keys (keyword-only without OpenAI, no expansion without Anthropic). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: scrub named references, add PG essay demo section to README Replace all Pedro/Brex/Jensen Huang/River AI examples with Paul Graham essay examples using the kindling corpus. Add "Try it" section to README showing the power of hybrid search on PG essays in 90 seconds. Update test fixtures to use concept pages instead of person pages. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-05 12:48:10 -07:00