feat: GBrain v0.7.0 — Integration Recipes + SKILLPACK Breakout (#39)
* docs: break SKILLPACK into 17 individual guides The 1,281-line SKILLPACK monolith is now 17 individually linkable guides in docs/guides/, organized by category: core patterns, data pipelines, operations, search, and administration. GBRAIN_SKILLPACK.md becomes a structured index with categorized tables linking to each guide. The URL stays stable for backward compatibility. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add integration guides, architecture docs, and ethos New documentation directories: - docs/integrations/ — "Getting Data In" landing page, credential gateway, meeting webhooks. Includes recipe format documentation. - docs/architecture/ — Infrastructure layer doc (import, chunk, embed, search) - docs/ethos/ — "Thin Harness, Fat Skills" essay with agent decision guide - docs/designs/ — "Homebrew for Personal AI" 10-star vision document Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add gbrain integrations command + voice-to-brain recipe New CLI command: gbrain integrations (list/show/status/doctor/stats/test) - Standalone command, no database connection needed - Uses gray-matter directly for recipe parsing (not parseMarkdown) - --json flag on every subcommand for agent-parseable output - Bare command shows senses/reflexes dashboard - Health heartbeat via ~/.gbrain/integrations/<id>/heartbeat.jsonl First recipe: recipes/twilio-voice-brain.md - Phone calls create brain pages via Twilio + OpenAI Realtime - Opinionated defaults: caller screening, brain-first lookup, quiet hours - Outbound call smoke test (GBrain calls the user to prove it works) - Validate-as-you-go credential testing - Twilio signature validation for webhook security Migration file for v0.7.0 with agent-readable changelog. 13 unit tests covering parseRecipe, CLI routing, and recipe validation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add Getting Data In to README, update CLAUDE.md and manifest README: voice calls in intro bullet list, new "Getting Data In" section with integration table (voice, email, X, calendar) and recipe philosophy. CLAUDE.md: reference new files (integrations.ts, recipes/, docs/guides/, docs/integrations/, docs/architecture/, docs/ethos/). manifest.json: bump to v0.7.0, add recipes_dir field. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: v0.7.0 CHANGELOG, TODOS, VERSION bump CHANGELOG: v0.7.0 entry covering integration recipes, voice-to-brain, gbrain integrations command, SKILLPACK breakout, and new documentation. TODOS: 3 new items from CEO/DX reviews (constrained health_check DSL, community recipe submission, always-on deployment recipes). VERSION + package.json: bump to 0.7.0. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: rewrite voice recipe with agent instructions and verified links Major improvements to recipes/twilio-voice-brain.md: - Agent preamble: explains WHY sequential execution matters (each step depends on the previous), defines 4 stop points where the agent MUST pause and verify, tells agent to never say "something went wrong" but instead explain the exact error and fix - User actions are now specific: exact URLs for every credential (Twilio console, OpenAI API keys page, ngrok dashboard), what buttons to click, what fields to copy, common failure modes - All URLs verified via web search against current 2026 documentation: Twilio SID/token at twilio.com/console, OpenAI keys at platform.openai.com/api-keys, ngrok token at dashboard.ngrok.com/get-started/your-authtoken - Cost estimate corrected: OpenAI Realtime is $0.06/min input + $0.24/min output (was understated), total ~$20-22/mo for 100 min - Validate-as-you-go: each credential tested immediately with exact curl commands, failure messages explain what went wrong and how to fix - Smoke test flow: tells user exactly what to say, verifies ALL three outputs (messaging notification + brain page + search result) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add "Homebrew for Personal AI" essay (markdown is code) New essay at docs/ethos/MARKDOWN_SKILLS_AS_RECIPES.md — the distribution corollary to "Thin Harness, Fat Skills." Argues that markdown skill files are simultaneously documentation, specification, package, and source code. The agent is the package manager. The git repo is the app store. Referenced from SKILLPACK index and CLAUDE.md. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: rewrite agent instructions as command language, promote skills The OpenClaw/Hermes install block is now a drill sergeant, not a tour guide. Every step is an imperative command with exact verification criteria and explicit stop-on-failure behavior. No FYI, no suggestions, just rails. Key changes: - 11-step setup with STOP points after each step - Exact user instructions for Supabase connection string (what to click, what NOT to give the agent, what the string looks like) - "Verify: run X. You must see Y. If not: Z" after every step - Skills table now links to both skill files AND guide docs - Integration recipes table simplified (no "coming soon" placeholders) - Docs section reorganized: for agents / for humans / reference Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 4 codex findings + add email-to-brain recipe Codex review found 4 issues, all fixed: 1. getStatus() returned "configured" if ANY secret was set (e.g. just OPENAI_API_KEY). Now requires ALL required secrets before marking configured. Prevents false "configured" status and spurious doctor runs. 2. Twilio health check hit unauthenticated endpoint (always 401). Now uses authenticated curl with SID:token, matching the setup validation. 3. README anchor docs/GBRAIN_SKILLPACK.md#the-dream-cycle broken after SKILLPACK rewrite. Updated to point to docs/guides/cron-schedule.md. 4. Compiled binary can't find recipes/ via import.meta.dir. Added GBRAIN_RECIPES_DIR env var override + global bun install path fallback. Also adds recipes/email-to-brain.md: Gmail deterministic collector pattern with ClawVisor credential gateway, validate-as-you-go, agent instructions. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add email, X, calendar, and meeting sync recipes Four new integration recipes extracted from production wintermute patterns: - recipes/email-to-brain.md: Gmail via ClawVisor, deterministic collector pattern (code pulls emails with baked-in links, agent does judgment), noise filtering, signature detection, digest generation - recipes/x-to-brain.md: X API v2, timeline + mentions + keyword search, deletion detection (diffs previous run, verifies 404), engagement velocity tracking, rate limit awareness - recipes/calendar-to-brain.md: Google Calendar via ClawVisor, historical backfill (years of data), daily markdown files with attendees + locations, attendee enrichment for brain pages - recipes/meeting-sync.md: Circleback API, transcript import with speaker labels, attendee detection + filtering, entity propagation to people/ company pages, action item extraction, idempotent by source_id All recipes follow the same format: agent preamble with sequential execution rules, validate-as-you-go credentials, exact URLs for API key setup, stop-on-failure verification, and heartbeat logging. Updated README, SKILLPACK index, and integrations landing page with all 5 recipes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add Google OAuth as alternative to ClawVisor in email + calendar recipes Both recipes now offer two auth options: - Option A: ClawVisor (recommended, handles OAuth + token refresh) - Option B: Google OAuth2 directly (no extra service, you manage tokens) Option B includes step-by-step instructions for Google Cloud Console: exact URLs, which buttons to click, which scopes to add, how to enable the API, and the OAuth flow for token exchange. This removes ClawVisor as a hard dependency for getting started. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add implementation guides with pseudocode and test suggestions Every recipe now includes an "Implementation Guide" section with: - Production-tested pseudocode the agent can follow to build each collector - Edge cases and failure modes discovered in real deployment - Non-obvious implementation details (why the 48h staleness heuristic, why Gmail links need authuser, why SSE responses need double-parsing) - Test suggestions: what the agent should verify after setup email-to-brain: noise filtering algorithm, signature detection patterns, Gmail link generation (authuser is critical), sent-mail dedup x-to-brain: deletion detection with 3 heuristics (7-day, 48h staleness, API verification), engagement velocity thresholds (50 min for 2x, 100 absolute jump), atomic writes, stdout contract, rate limit handling calendar-to-brain: smart chunking (monthly for sparse years, weekly for dense), attendee filtering (rooms, groups, distros), merge-with-existing (only replace ## Calendar section), date/time parsing edge cases meeting-sync: SSE double-JSON parsing, idempotency double-check (grep + filename), auto-tagging from meeting names, git commit after sync Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: 6 new guides from production patterns (wintermute extraction) New guides extracted and generalized from production deployment: - repo-architecture.md: Two-repo pattern (agent behavior vs world knowledge). Strict boundary rules, decision tree, hard rule: never write knowledge to the agent repo. - sub-agent-routing.md: Model routing table by task type. Signal detector pattern (spawn Sonnet on every message). Research pipeline pattern (Opus plans, DeepSeek executes, Opus synthesizes). Cost optimization. - skill-development.md: 5-step cycle (concept, prototype, evaluate, codify, cron). MECE discipline (no overlapping skills). Quality bar checklist. "If you ask twice, it should already be a skill." - idea-capture.md: Originality distribution rating (0-100 across 4 populations). Depth test ("could someone unfamiliar understand WHY?"). Deep cross-linking mandate. Notability filtering. - quiet-hours.md: Hold notifications 11pm-8am local time. Held messages directory pattern. Timezone-aware delivery. Morning briefing pickup. - diligence-ingestion.md: 9-step pipeline for data room materials. Detection patterns (PDF filenames, spreadsheet tabs, user language). Index.md template with bull/bear case. Company page enrichment. All PII scrubbed. Patterns generalized for any user. SKILLPACK index updated with 6 new entries. CLAUDE.md references added. All 37 SKILLPACK links verified. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: upgrade all guides to operational playbooks with pseudocode Every guide now follows the playbook structure: - Goal: one sentence, what this achieves - What the User Gets: without this / with this - Implementation: pseudocode with actual gbrain commands - Tricky Spots: production-tested gotchas - How to Verify: test steps the agent runs after setup Guides upgraded (15 files): - brain-agent-loop: on_message() loop with read/write/sync pseudocode - brain-first-lookup: 4-step lookup cascade with exact commands - brain-vs-memory: routing algorithm for 3 knowledge layers - compiled-truth: page structure + rewrite vs append rules - content-media: 3 ingest patterns (YouTube, social, PDFs) - cron-schedule: full schedule table + dream cycle pseudocode - enrichment-pipeline: 7-step protocol with tier classification - entity-detection: spawn pattern + detection prompt + notability filter - executive-assistant: 3 workflow algorithms (triage, prep, post-inbox) - meeting-ingestion: 6-step transcript-to-brain flow - operational-disciplines: 5 executable discipline blocks - originals-folder: detection + exact-phrasing capture + cross-linking - search-modes: decision tree for keyword vs hybrid vs direct - source-attribution: citation format + hierarchy + conflict resolution - Plus Goal/What User Gets headers on 6 newer guides Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add WebRTC to voice recipe + ngrok Hobby setup guide Voice recipe updates: - Added WebRTC endpoint (POST /session, GET /call, POST /tool) for browser-based calling with RNNoise noise suppression - WebRTC pseudocode with the 4 non-obvious gotchas from production (voice under audio.output.voice, no turn_detection, no session.update on connect, trigger greeting via data channel) - Recommend ngrok Hobby ($8/mo) for fixed domain instead of free tier - Fixed domain means URLs never change, Twilio never breaks New guide: docs/mcp/NGROK_SETUP.md - How to set up ngrok Hobby for both MCP and voice agent - Fixed domain setup, watchdog pattern, AI client configuration - Claude Desktop requires Settings > Integrations (not JSON config) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add dependency graph + ngrok-tunnel + credential-gateway recipes Recipes now have real dependencies via the `requires` field: - voice-to-brain requires ngrok-tunnel (needs public URL for Twilio) - email-to-brain requires credential-gateway (needs Gmail access) - calendar-to-brain requires credential-gateway (needs Calendar access) - x-to-brain and meeting-sync are standalone (direct API keys) Two new infrastructure recipes: - ngrok-tunnel: fixed public URL for MCP + voice. Recommends Hobby ($8/mo) for a domain that never changes. Includes watchdog pattern. - credential-gateway: secure Google service access via ClawVisor (recommended) or direct OAuth2. One setup, all Google recipes use it. Moved ngrok from docs/mcp/ to recipes/ — it's shared infrastructure, not MCP-specific. README and integrations landing page show dependency chains. When agent installs voice-to-brain, it sets up ngrok-tunnel first. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: add infra category, fix dashboard alignment, show dependencies DX audit found two bugs in gbrain integrations dashboard: 1. Column alignment broken — IDs > 18 chars ran into descriptions with no space. Fixed: pad to 22 chars. 2. ngrok-tunnel and credential-gateway showed as SENSES but they're infrastructure. Added 'infra' category. Dashboard now shows three sections: INFRASTRUCTURE (set up first), SENSES, REFLEXES. 3. Dependencies now shown inline: "AVAILABLE (needs credential-gateway)" Also added 'requires' field to JSON output for agent consumption. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add frontier model requirement disclaimer to README GBrain's markdown-is-code approach requires models capable of interpreting intent and implementing from architecture descriptions. Tested with Claude Opus 4.6 and GPT-5.4 Thinking. Smaller models will struggle with the recipe format. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add PGLite → Supabase upgrade path to README Clarify the database progression: start with PGLite (Postgres as WASM, zero infrastructure, pgvector built in, nothing to install). Graduate to Supabase or self-hosted Postgres when you need connection pooling, concurrency, and remote MCP access from Claude Desktop, Cowork, ChatGPT, Perplexity Computer, or any MCP-compatible agent. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: revert PGLite mention (coming in next branch) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: make all 23 guides consistent (Goal/Impl/Tricky/Verify) Every guide now has exactly these sections in this order: - ## Goal (one sentence) - ## What the User Gets (without this / with this) - ## Implementation (pseudocode with gbrain commands) - ## Tricky Spots (3-5 numbered gotchas) - ## How to Verify (3-5 numbered test steps) 11 guides restructured from non-standard headings: - deterministic-collectors, live-sync, upgrades-auto-update (full rewrites) - entity-detection, diligence-ingestion, idea-capture, quiet-hours, repo-architecture, skill-development, sub-agent-routing (restructured) 23/23 guides now pass consistency audit. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: restructure README around the #1 blocker (getting data in) The README was leading with Postgres and database architecture. Most users are stuck at step zero: "I have an agent but it doesn't know anything about my life." New structure: 1. The Problem — your agent doesn't know your life 2. Getting Data In — integration recipes, front and center 3. The Compounding Thesis — why this matters 4. How this happened — credibility, origin story 5. When you need Postgres — scale, not starting point Postgres is de-emphasized from a full section to two paragraphs: "You don't need Postgres to start" and "When you need Postgres" (1,000+ files, remote MCP access, multiple AI clients). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: move Install to top of README, remove duplicate section Install now appears right after Getting Data In (line 38), not buried at line 295. The user sees: Problem → Getting Data In → Install. Removed the duplicate Install section (262 lines) that was lower in the README. The agent instructions block, CLI quickstart, and all content is now in the single Install section near the top. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: move agent install block to first thing in README "Start here: paste this into your agent" is now the first section, right after the one-line pitch. No scrolling, no context, no preamble. User opens the README, sees the paste block, copies it into OpenClaw or Hermes, and the agent takes over. Flow: pitch → paste block → Getting Data In → Compounding Thesis → origin story Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: compress install block from 11 steps to 5 The agent install block was 102 lines and 11 steps. Now it's 40 lines and 5 steps. Same coverage, half the text. Changes: - Merged "prove keyword search" + "embed" + "prove hybrid search" into one SEARCH step (the user doesn't care about the intermediate) - Merged skillpack, sync, auto-update, integrations, verification into one GO LIVE step with sub-items (post-install polish, not install) - Shortened database instructions (one line instead of 5 sub-steps) - Removed redundant preamble ("YOU MUST COMPLETE EVERY STEP" is now just "Do not skip steps. Verify each step.") The 5 steps: INSTALL → DATABASE → IMPORT → SEARCH → GO LIVE Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * security: gitignore all .env files, not just specific ones CSO audit found .gitignore covered .env.testing and .env.production but not bare .env. A user creating .env with database credentials could accidentally commit it. Fix: .env and .env.* are now gitignored. .env.*.example files are explicitly un-ignored so templates remain tracked. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * security: scrub PII from essay and recipe examples - 510-MY-GARRY phone mnemonic → "Your Phone Number" - "Garry → Authenticated Mode" → "Owner → Authenticated Mode" - "Telegram" → "secure channel" in auth example - @garrytan → @yourhandle in X recipe example Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Garry Tan
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docs/guides/search-modes.md
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docs/guides/search-modes.md
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# Search Modes
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## Goal
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Know which search command to use and when -- keyword, hybrid, or direct -- so every lookup is fast and returns the right result.
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## What the User Gets
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Without this: the agent fumbles between search commands, returns chunks when full pages are needed, runs expensive semantic searches when a direct get would do, or misses results entirely. With this: every lookup uses the optimal mode, token budgets are respected, and the user gets the right information in the fewest calls.
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## Implementation
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```
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on user_asks_about(topic):
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# Decision tree: pick the right search mode
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if know_exact_slug(topic):
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# MODE 3: Direct get -- instant, no search overhead
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result = gbrain get <slug>
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# e.g., "Tell me about Pedro" -> gbrain get pedro-franceschi
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# Returns the FULL page -- compiled truth + timeline
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elif topic.is_exact_name or topic.is_keyword:
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# MODE 1: Keyword search -- fast, no embeddings needed, day-one ready
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results = gbrain search "{name_or_keyword}"
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# e.g., "Find anything about Series A" -> gbrain search "Series A"
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# Returns CHUNKS, not full pages
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# IMPORTANT: keyword search returns chunks
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# If the chunk confirms relevance, THEN load the full page:
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if chunk.confirms_relevance:
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full_page = gbrain get <slug_from_chunk>
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elif topic.is_semantic_question:
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# MODE 2: Hybrid search -- semantic + keyword, needs embeddings
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results = gbrain query "{natural language question}"
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# e.g., "Who do I know at fintech companies?" -> gbrain query "fintech contacts"
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# Returns ranked chunks via vector + keyword + RRF
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# Same rule: chunks first, then get full page if needed
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if chunk.confirms_relevance:
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full_page = gbrain get <slug_from_chunk>
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# Quick reference:
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# | Mode | Command | Needs Embeddings | Speed | Best For |
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# |---------|----------------------|------------------|---------|---------------------------------|
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# | Keyword | gbrain search "term" | No | Fastest | Known names, exact matches |
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# | Hybrid | gbrain query "..." | Yes | Fast | Semantic questions, fuzzy match |
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# | Direct | gbrain get <slug> | No | Instant | When you know the slug |
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# Progression over time:
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# Day 1: keyword search (works without embeddings)
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# After first embed: hybrid search unlocked
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# Once you know slugs: direct get for speed
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# Precedence for conflicting information within a page:
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# 1. User's direct statements (always wins)
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# 2. Compiled truth sections (synthesized from evidence)
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# 3. Timeline entries (raw signal, reverse chronological)
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# 4. External sources (web search, APIs)
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```
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## Tricky Spots
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1. **Search returns chunks, not full pages.** After `gbrain search` or `gbrain query`, you get excerpts. Always run `gbrain get <slug>` to load the full page when the chunk confirms relevance. Don't answer questions from chunks alone when the full context matters.
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2. **Keyword search works without embeddings.** On day one before any embedding run, `gbrain search` still works. Don't tell the user "search isn't available yet" -- keyword search is always available.
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3. **Don't use hybrid search for known names.** `gbrain query "Pedro Franceschi"` wastes embedding compute. Use `gbrain search "Pedro Franceschi"` or better yet `gbrain get pedro-franceschi` if you know the slug.
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4. **Token budget awareness.** A full page via `gbrain get` can be large. Read the search chunks first to confirm relevance before pulling the full page. "Did anyone mention the Series A?" -- search results (chunks) are probably enough. "Tell me everything about Pedro" -- get the full page.
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5. **Hybrid search needs embeddings to have been run.** If `gbrain query` returns nothing but `gbrain search` finds results, the embeddings haven't been generated yet. Run the embedding pipeline first.
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## How to Verify
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1. Run `gbrain search "Pedro"` -- confirm it returns chunks with matching text and slug references.
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2. Run `gbrain query "who works at fintech companies"` -- confirm it returns semantically relevant results (not just keyword matches on "fintech").
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3. Run `gbrain get pedro-franceschi` -- confirm it returns the full page with compiled truth and timeline.
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4. Compare: search for the same entity using all three modes. Keyword should be fastest, hybrid should surface conceptual matches, direct should return the complete page.
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5. After a search returns a chunk, run `gbrain get` on the slug from that chunk. Confirm the full page contains more context than the chunk alone.
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---
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*Part of the [GBrain Skillpack](../GBRAIN_SKILLPACK.md).*
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