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Create new skills following the GBrain conformance standard. Generates SKILL.md with frontmatter, Contract, Phases, Output Format, and Anti-Patterns. Checks MECE against existing skills. Updates manifest and resolver.

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Save and load timestamped reports. Keyword routing for fast lookup. Cron jobs save output as reports; the agent or user queries them by keyword. Includes the Actionability Gate: delivery-time link checks (Broken/Dead/Indirect/ Missing) for briefings, meeting digests, and research reports.

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Evolve your brain's schema pack. Add page types, propose new ones from corpus scans, backfill page.type on existing pages, audit pack health. Triggers when an agent notices untyped pages, custom domains needing typed entities (researcher, contract, deposition), or wants to see what types the pack declares.

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Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler. Collapses 94 noisy types to 15 canonical with subtypes, alias rows, and link rows. Triggers when an agent notices pack_upgrade_available, type_proliferation, or asks "what is the canonical taxonomy / how do I clean up my page types".

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Author an eval for an existing skill from its REAL usage history, not its spec. Mine invocations from the brain's conversation archive (conversations/) and per-harness session transcripts — a user correction after an invocation is the gold signal — then synthesize an eval_contract plus 4-8 replayable cases with honesty labels (SPEC-DERIVED vs HISTORY-IMPLIED) and stage the result at skills/<name>/eval/autobench-<date>.md as PENDING-HUMAN-APPROVAL. Never rewrites SKILL.md. Ships two guard companions: panel integrity (multi-model judging must prove each provider actually responded) and the fail-improve taxonomy (logged LLM-fallback cases convert to deterministic code over time).

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Run `gbrain skillpack-check` to produce an agent-readable JSON health report for the gbrain install. Wraps `gbrain doctor` + `gbrain apply-migrations --list` so a host agent (your OpenClaw's morning-briefing, any OpenClaw cron) can see at a glance whether the skillpack needs attention. Use when the user asks "is gbrain healthy?", when a cron fires a morning check, or proactively when something seems off (jobs not running, brain not updating, autopilot silent).

日本語の概要は準備中です。原文の説明を表示しています。

Self-evolving skill optimization via SkillOpt-paper-grounded text-space optimizer.

日本語の概要は準備中です。原文の説明を表示しています。

Where new brain files go. Decision protocol for filing brain pages by primary subject, not by format or source. Reference for all brain-writing skills.

日本語の概要は準備中です。原文の説明を表示しています。

Reference skill demonstrating the 10/10 skillpack contract. Adds a "what does this skillpack do" answer to the user's agent.

日本語の概要は準備中です。原文の説明を表示しています。

Tiered LLM extraction pattern for large corpus processing (email archives, document dumps, transcript libraries). A utility-tier model triages and classifies at speed; the reasoning tier does the default deep read; the deep tier is the escalation for the highest-value content. Prevents spending deep-tier money on noise while ensuring the important content gets the best eyes. A deterministic privacy wall runs before any LLM call.

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Deep-research a topic end to end and produce a permanent, reusable knowledge asset: archive every primary source verbatim (gated by the user's privacy/retention posture), write one 1:1 summary per source, then synthesize a single self-contained compendium page. Depth is a dial (base synthesis → grounded primaries → books + counter-canon → saturation), each level an idempotent superset of the one below. Distinct from data-research (structured trackers) and perplexity-research (web deltas): this produces prose knowledge synthesis backed by an archived source corpus.

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Publish the user's own gbrain over MCP so other devices, desktop apps and cloud agents can reach it. `gbrain mcp expose` installs and signs in Tailscale, publishes the running `gbrain serve --http` on the tailnet (HTTPS, tailnet-only by default; Funnel only when a client lives in a vendor cloud), keeps the server alive as a user service, and hands back the MCP URL. Then register one least-privilege client per consumer, choose native OAuth/PKCE or a private machine handoff for that client, and verify the connection inside the intended harness.

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Search and write the company knowledge brain. Use for any question about the org, people, projects, decisions, or history, and to persist durable knowledge beyond this scope's notebook.

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Share brain pages as beautiful password-protected HTML with zero LLM calls

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Gate on identity questions to the user. Before any "who is X?" (or role / relationship question) reaches the user, exhaust the brain's lookup chain: think → search + page read → mounted sources → timeline/graph → web. If escalation survives the chain, ask WITH a hypothesis, never a bare unknown. Also owns the no-placeholders-at-ingest rule: pages created during bulk ingestion get their relationship/role resolved immediately.

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Health smoke tests + auto-fix for gbrain installs (and OpenClaw services when present). Run after machine/container restarts or whenever something seems broken. Tests critical services, auto-fixes bounded local issues, and reports worker topology without starting daemons. Extensible via user-defined test scripts in ~/.gbrain/smoke-tests.d/*.sh.

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Generic framework for converting external events (SMS, meetings, social mentions) into brain-ingestible signals. Define a transform function, register a webhook URL, and incoming events get processed through the brain pipeline.

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Route to Mars (introspective thought partner / demo showman voice persona). Used when the operator wants depth, meaning, or impressive social demos rather than logistics. Mars handles SOLO mode (philosophy, presence, patterns) and DEMO mode (tool-driven showmanship) automatically.

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Ingest a voice note with exact-phrasing preservation (never paraphrased). Routes content to originals/, concepts/, people/, companies/, ideas/, personal/, or voice-notes/ based on a decision tree. The user's exact words are the signal.

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Re-run or deepen the agent's identity interview. Drives the SHARED bootstrap answer bank (state/interview.json) via `gbrain bootstrap interview --set/--show/--confirm`, then re-renders the identity files with `gbrain bootstrap render --only <FILE> --force`. One answer store, two surfaces: first-boot bootstrap and this re-run skill write the same bank, so an updated answer flows into SOUL.md, USER.md, ACCESS_POLICY.md, and HEARTBEAT.md without hand-editing rendered files. Every answer is the user's own words — never invented.

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The meta skill. Turn any raw feature into a properly-skilled, tested, resolvable unit of agent capability. Idempotent: running on an existing skill improves it (bug fix, new input, quality pass) instead of starting from scratch. Every skill declares an EVAL CONTRACT (its goal + skill-specific dimensions + hard-fails) so the cross-modal eval judges THIS skill's real purpose, not generic slop. Cross-modal eval runs BEFORE tests: 3 frontier models from different providers critique the output against the contract, you iterate to quality, THEN write/update tests that lock in the proven-good behavior. NO-REGRESSION LAW: any edit to a skill must score >= the previous iteration's eval — forward only, never back. For skills that back a scheduled job, an edit MUST re-run a representative task and eval it before shipping.

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Extract a sanitized shared team/company brain from a personal brain. Strips internal ratings, compensation, performance assessments, retention and political dynamics from pages, takes, and facts across the full scan scope (people, companies, meetings, dailies, cross-references — not just people/), verifies with grep + retrieval passes, and purges sensitive git history behind the data-loss-gate confirmation card. Also runs as a report-only re-audit on an existing shared brain.

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Systematic claim-by-claim verification for any content before it ships. Modeled on professional fact-checking desks (The New Yorker, ProPublica, IFCN standards): extract every verifiable claim, check each against live citable sources (never training data), assign a 6-level confidence status, apply corrections, and produce a scored pass/fail report. Includes a data-derived-claims gate for outputs produced FROM the brain or a database: PRODUCER ≠ VERIFIER (re-derive each claim via a different query path) and AFFILIATION ≠ AUTHORSHIP (person→thing claims resolve through typed edges), with delivery hard-blocked on unsupported claims.

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Transform raw article text dumps in the brain into structured pages with executive summary, verbatim quotes, key insights, why-it-matters, and cross-references. Replaces walls-of-text with quotable, actionable brain pages.

日本語の概要は準備中です。原文の説明を表示しています。