テスト・セキュリティのスキル

Run bounded, read-only semantic advisory sidecar passes for candidate mapping, issue triage, upstream diffs, evidence verification triage, and meta audit hints. Enforces monthly spend limits with explicit fallback to worker-luna.

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Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.

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Phase 2 of the evidence verification pipeline. Validates GitHub star counts in registry skill files against live GitHub API data and flags stale or inflated metrics without repartitioning evidence by rank. Use this after /ev-collection has compiled the unified data lake and before /ev-adversarial-audit begins. Trigger phrases: "verify stars", "check star counts", "refresh stargazer metrics", "run star verification", "ev-star-verification", "Phase 2", "live star check".

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Phase 2B of the Gaia evidence verification pipeline. Verifies benchmark-result rows and benchmark-source candidates against registry/benchmark-sources.json before adversarial audit, link validation, catalog promotion, or ingestion. Use when running /ev-pipeline, checking benchmark-result evidence, reviewing benchmark-source candidates, or preparing benchmark rows for /gaia-ingest-batch.

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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.

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Top-level orchestrator for the Gaia Skill Tree evidence verification pipeline. Run this when you want to do a full evidence pass — collecting raw sources, verifying live GitHub star counts, running Phase 2B benchmark-source verification, adversarially auditing for quality/formatting issues, and checking that every URL is reachable — all in one coordinated sequence. Trigger phrases: "run the evidence pipeline", "full evidence pass", "verify evidence", "evidence verification pipeline", "run ev-pipeline", "check all evidence", "audit the data lake", "evidence quality sweep", "refresh evidence", "validate evidence sources". Also aliased as /evidence-verification-pipeline. Use the individual sub-skills (ev-collection, ev-star-verification, ev-adversarial-audit, ev-link-validation) only when you need to re-run one phase in isolation; for end-to-end work, always start here.

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Audit and repair Gaia user-tree timelines so every skill's current rank is explained by a chain of Hero's Journey events. Trigger this skill when: a contributor's profile chart shows a stale rank (e.g. still shows 3★ after a demotion to 1★); someone asks to "trace what happened" to a skill's rank; `validate_timelines.py` is failing in CI; you need to backfill missing `demote` or `rank_up` events before cutting a release; a skill was reclassified or Star-Bar-reset and the user tree was never updated; or any time the registry node and user tree disagree on a skill's current level. Uses `scripts/trace_timeline.py` (dry-run + apply) and `scripts/validate_timelines.py` (CI gate). Do NOT hand-edit `timeline[]` arrays — the script synthesises properly labelled events with `previousValue`/`newValue` so the rank chart plots correctly.

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Appraise the complete post-ingest Gaia tree: run 13 deterministic audit dimensions, recompute evidence, Trust Magnitude and rank eligibility, use Jev/Luna for bounded semantic review, adversarially verify findings, and report structural proposals. Gaia computes authority; Jev is read-only advice; humans ratify all mutations. Use for a registry-wide sweep, full meta audit, evidence/rank review, fusion candidates, generic proposals, or a durable findings report. This is the macro companion to /gaia-meta-audit (prioritized queue) and /gaia-audit (single skill).

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Generate a prioritized review queue of registry skills and catalog items that need attention. Use this skill whenever someone asks: "what needs review?", "what's overdue for audit?", "where are the weak spots in the registry?", "what should I audit next?", "run a health check on the registry", "show me flagged skills", "find problems in the registry", "what skills need fixing?", or "triage the registry". This is the triage layer — it surfaces candidates ranked P0–P4 so that focused work (via /gaia-audit) targets the right things first. Run this before any audit pass. Also invoke proactively when a PR changes registry/named/ at scale, or before a release, to catch regressions early.

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Comprehensive, reusable playbook for multi-component suite intake under Yggdrasil III. Audits component installability, maps origin candidates to generic capabilities, ingests named components with shared-repo baseline caps, manifests suites via gaia dev fuse, calibrates capstone and component ranks, and closes out via Class S regeneration.

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Focused single-target audit of one Gaia skill, named skill, or real-skill catalog item. Use this skill when: auditing a specific skill by ID or name, a skill looks overpromoted, evidence feels thin or dead, a contributor's skill seems outdated or superseded, the rank doesn't match the source quality, evidence is mapped to the wrong Evidence Type, a skill at 3★+ is missing a working GitHub link, someone asks "does this skill deserve its stars?", or you want the smallest possible correction with validation — not a bulk sweep. This is NOT for bulk curation passes (use /gaia-curate for that) or meta-level registry sweeps (use /gaia-meta-audit). It is specifically for "fix this one skill, get it right."

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Phase 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.

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Explore a feature or CLI, repair verified defects, review adversarially, and leave one existing or new PR ready for its authorized reviewer. Use for "explore X", "test and ship X", "run the pipeline on X", "stress-test X", or "take X through the full pipeline" when exploration and integration matter. Supports lean autonomous, structured economy (default), and explicit hard-gated runs. Routine checkpoints do not require user approval; actual founder, L4, security, schema and merge gates always apply. Not for a one-file edit with no exploration need. Uses scripts/state.sh for resumable checkpoints.

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Use when a task needs the judgment of an electric-motor and power-tool repairer — reading a megohmmeter/polarization-index test to catch a winding fault before failure, deciding rewind vs. replace on a failed induction motor, isolating a bearing fault from a broken-rotor-bar fault, judging brush/commutator wear on a universal motor, or evaluating whether a rewind was actually done to spec.

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Use when a task needs the judgment of an Electromechanical Equipment Assembler — verifying shaft/coupling alignment directly rather than trusting an initial functional test that only confirms the device runs, applying fastener torque to spec with a calibrated tool rather than by feel, routing wire to account for the equipment's full range of motion rather than its static assembled position, or distinguishing electrical from mechanical root cause when a device malfunctions.

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Use when a task needs the judgment of an Economist — estimating a demand elasticity or causal treatment effect from observational or experimental data, building a cost-benefit or welfare analysis for a policy or pricing decision, forecasting a macro or market aggregate under stated assumptions, or stress-testing whether a "the data shows X" claim survives a confounding-variable check.

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Use when a task needs the judgment of an Electrical and Electronic Equipment Assembler — inspecting a solder joint against the specific IPC/J-STD workmanship standard criteria rather than personal visual judgment, following ESD precautions for every component handled since damage is invisible at the time it occurs, verifying a crimped connection with a pull test rather than visual inspection alone, or treating a single suspected cold joint as a potential complete failure point rather than a minor defect.

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Use when a task needs the judgment of an Epidemiologist — investigating a disease outbreak and identifying its source, designing a case-control or cohort study to test an exposure hypothesis, calculating attack rates/odds ratios/relative risk from surveillance data, evaluating whether a surveillance system is sensitive and timely enough to catch a real signal, or judging whether an observed case cluster is a true outbreak or expected background variation.

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Use when a task needs the judgment of an Electromechanical Technician — meggering a motor and reading polarization index, zone-classifying a vibration reading against ISO 10816/20816, decay-testing a pneumatic cylinder, pull-testing a crimp against IPC/WHMA-A-620, diagnosing a PLC rung that "looks right but won't fire," or selecting arc-flash PPE category before opening an enclosure.

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Use when a task needs the judgment of an Equal Opportunity Representative or Officer — running an adverse-impact analysis on hiring or promotion selection rates, conducting an availability analysis to set affirmative action placement goals, evaluating a compensation-equity regression for unexplained pay gaps, or preparing an affirmative action plan (AAP) for an OFCCP audit.

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Use when a task needs the judgment of an Engine and Other Machine Assembler — following the specified multi-stage torque sequence for a multi-bolt joint rather than tightening bolts to final value in convenient order, measuring bearing clearance directly rather than confirming free rotation by hand, verifying critical clearances on the actual assembled stack-up rather than trusting individually-in-tolerance components, or testing sub-assemblies before final integration rather than only at final test.

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Use when a task needs the judgment of an Energy Engineer working on building and industrial energy efficiency — running an ASHRAE Level 1/2/3 energy audit, calculating envelope heat loss/gain with the degree-day method, comparing HVAC equipment on SEER/EER/IEER/COP rather than nameplate alone, designing an IPMVP measurement and verification (M&V) plan, or ranking energy conservation measures (ECMs) by savings-to-investment ratio for a capital plan. Distinct from a wind-energy-engineer or solar/PV engineer (own generation-asset design and yield) and from an electrical-engineer (owns utility-scale power delivery and protection) — this role owns the demand side: how much energy a building or process actually needs, and which retrofit reduces that number with numbers that hold up after the fact.

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Use when a task needs the judgment of an Energy Auditor — running a blower-door/duct-leakage diagnostic sequence on a home or light-commercial building, testing combustion appliances for worst-case backdraft risk before recommending air sealing, reconciling utility billing history against walkthrough findings, ranking retrofit measures by savings-to-investment ratio (SIR) for a weatherization or utility rebate program, or writing the prioritized scope of work an install crew executes without the auditor on site. Distinct from an energy-engineer (industrial/commercial capital planning, IPMVP measurement and verification, calibrated simulation) — this role owns the field diagnostics and the residential/light-commercial audit-to-scope handoff.

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Use when a task needs the judgment of a licensed elevator mechanic — diagnosing a governor or safety-circuit fault, planning or witnessing a Category 1/Category 5 periodic test, sequencing an elevator or escalator installation/modernization to code, or deciding whether equipment can stay in service pending a repair.

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。