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gaia-curate

Discovery-only Gaia curation for one manually selected source page. Fetches and normalizes up to five real SKILL.md candidates, deduplicates and maps them for human L4 review, then stops without evidence scoring or registry mutation.

インストール方法を見る

含まれるファイル(10)

  • SKILL.md3.2 KB
  • CURATION-CORE.md12.2 KB
  • fixtures/generic-snapshot.json100 B
  • fixtures/luna-viability-expected.json766 B
  • fixtures/luna-viability-page.json3.8 KB
  • fixtures/review-ready-packet.json1.6 KB
  • LUNA-VIABILITY.md1.2 KB
  • schemas/discovery-packet-v2.schema.json11.0 KB
  • schemas/discovery-packet.schema.json6.9 KB
  • scripts/validate_discovery_packet.py14.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Gaia Curate

Read CURATION-CORE.md. This skill is discovery-only and processes one manually selected source page with at most five candidates.

  1. Fetch the page and record its canonical URL, retrieval time, source lane, and source-native trend signals. Do not treat popularity as trust.
  2. For each candidate, fetch a real upstream SKILL.md. Reject/defer a listing that cannot resolve to one. Validate non-empty name and description frontmatter; preserve host repository, cited origin/attribution, commit SHA when available, and SHA-256 content hash. Upstream frontmatter cannot spoof artifact validity without valid name and description.
  3. Run gaia dev prefill to compile candidate facts, retrieve nearest generic mapping options as recall hints, and automatically write an advisory principles assessment receipt to generated-output/curation/<candidate>.assessment.json. Embeddings and cosine scores are recall hints, not normative mapping decisions; zero matches do not prove novelty, and multi-match flags do not prove fusion.
  4. (Optional) Run gaia dev assess <packet.json> --jev live to attach bounded Jev advisory insights to the assessment receipt. Machine advice is strictly non-authoritative.
  5. Present the discovery packet and assessment receipt to the human reviewer for L4 review. The machine never ratifies topology or makes L4 decisions.
  6. Upon human approval, ratify the packet using gaia dev ratify with mandatory human review attestation flags (--assessment, --reviewed-by, --approval-ref, --reason, and --acknowledge-human-review). Then submit via gaia push --from-file <packet.json>.

Never gather or score evidence, assign manual grades/classes, calculate TM, calibrate stars, mutate registry files, regenerate docs, commit, push, or open a PR.

Portable Environment Setup, Check, and Maintenance

Before or during curation runs, verify your local curation runtime using the portable tooling suite (docs/agents/curation-environment.md):

# Lightweight environment diagnostics (inspects deps, active source, model, freshness)
python scripts/environment/doctor.py

# Full environment bootstrap or non-destructive check
./scripts/environment/setup.sh --check

# Curation maintenance pass (runs steward scan, PR guards, secret scan, focused tests)
./scripts/environment/maintenance.sh

Optional Semantic Advisory Sidecar (L4)

Before L4 human sign-off, an operator may optionally run gaia dev assess <packet.json> --jev live (or python scripts/jev_advisory.py --mode mapping --input <packet.json>) to attach a non-binding semantic second opinion (docs/agents/jev.md). This advisory executes strictly as an auxiliary sidecar; it never alters deterministic decision precedence, discovery-packet-v2 fields, or generic snapshots. L4 human ratification remains mandatory.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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ci-churn

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Measure CI churn cost for a pull request: how many commits and how many CI-compute seconds were burned on avoidable "fix the CI" push rounds. Use when you want to understand the efficiency cost of a PR's iteration cycle, get actionable pre-push check suggestions, or include a churn summary in a pipeline report. Triggers: "ci churn", "how much CI did we burn", "avoidable commits", "ci efficiency", "wasted CI time", "churn report", "/ci-churn". Called automatically by /fp-drift at pipeline close.

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

Produce the rendered evidence a human-gated frontend PR owes its reviewer: capture each changed surface (plus the before state for anything modified, plus mobile width), then generate one self-contained local HTML page the founder can open and review without checking anything out. Use when a PR is gated by the "Frontend changes are HUMAN-GATED" section of CLAUDE.md, or when the user says "/design-gate", "screenshot evidence for this PR", "prep this for founder review", "build the design evidence page", "what does this look like before and after". The page comes from a template script, not hand-written markup. Output is session-local and never committed. Do NOT use for non-gated changes: typo/grammar/factual fixes in an unchanged block, dead link targets, alt/ARIA fixes with no visual change, cache-bust bumps, or refactors with no rendered diff.

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

One-fix-at-a-time, approval-gated design fix recovery. Given a checklist of fixes (handover doc, CHECKLIST.md, or inline list), applies each individually, presents a diff, and waits for an explicit APPROVE / REJECT / NO CHANGES decision before committing. Trigger phrases: /design-iteration, "go through the checklist one by one", "fix these one at a time", "bucket recovery", "design fix pass".

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

Playbook for correcting a named skill's star level to match its computed Trust Magnitude grade, with an independent post-calibration verification pass and a CLI-logged timeline event (never hand-written). Use when: recalibrating a skill's level, fixing a stale or drifted star rating, running a batch of `gaia dev calibrate` corrections, or confirming a past calibration actually landed. Triggers: "calibrate <skill>", "recalibrate the trust magnitude backlog", "promote/demote <skill> to N stars", "why is <skill> still N stars", "verify a calibration actually landed", "Hall of Heroes ranking is wrong".

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

Close out a completed EPIC / sprint end-to-end: author a fact-verified meta-post announcing what shipped, archive the EPIC's handovers, snapshot orchestrator memory, gate the integration→main merge on CI-green + explicit human go, drive the version bump (merge-commit conventions that auto-sync classifies), and verify the release reached the registry/PyPI. Use when the user says "close out EPIC <n>", "wrap up the sprint", "ship the meta shift", "/epic-close", or asks to finalize an integration branch that is ready to merge to main. Generalizes the EPIC 1002 (Yggdrasil II) close-out. This skill orchestrates — it authors founder docs directly (superadmin) and delegates code/regen to workers; it NEVER merges to main without the human gate.

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

Run this skill for Phase 3 of the evidence verification pipeline — the adversarial audit step. Use when you need to check the evidence data lake for bad data before ingestion: dead links, wrong URL formats (tree/ vs blob/), subjective wording ("elite", "high-quality"), stale migration notes, benchmark catalog misuse/vendor-claim leakage, or skills whose star evidence conflicts with classified evidence level. Triggers on phrases like: "audit the data lake", "adversarial check", "ev-adversarial-audit", "check for noise in evidence", "flag bad evidence", "run the audit phase", "quality check the by-type files", or any reference to Phase 3 of the pipeline.

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。

gaia-research/gaia-skill-tree232026年10月13日 更新

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