「evidence」の検索結果

Bug bounty findings secretary, tracker, and workspace initializer for the bb-huge portal. Use this skill for web security research, vulnerability hunting, and hunt workspace setup. Triggers on: "log finding", "save finding", "add to bb-huge", "record vulnerability", "update finding", "show findings", "bb-huge stats", "mark as confirmed", "mark as rewarded", "setup workspace", "pull evidence", "continue working on finding", "dump attachments", "list my skills", "what skills do I have", "/bb-huge init", "init hunt workspace", "new bug bounty program", "start hunting", "mobile bug bounty", "binary analysis", "source code review", "white-box audit", "h1-brain", "hack program", "hack()", "search disclosed", "fetch rewarded". Also auto-activates whenever a vulnerability is discovered during any recon, fuzzing, or manual testing session — do not wait to be asked.

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Review computational protein or gene function predictions and fill PredictionReview YAML files using the COR/CNN/LSP/UNC/PLI/NPI/REP biological-validity taxonomy. Use for ProtNLM, DeepECTF, BioReason/GO-GPT, InterPro2GO, PANTHER/IBA, CLEAN, GloEC, MAPred, ProteinInfer, or other predicted EC/GO annotations, including audits of the evidence and reasoning in existing prediction reviews.

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Use this agent when you need to systematically review existing GO annotations for a gene and make curation decisions based on literature evidence and functional analysis. This agent should be called after seeding the SPECIES/GENE/GENE-ai-review.yaml file, which seeds each annotation with `action: PENDING`; these should all be manually reviewed.

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Review AI Gene Review pull requests and curation changes for GO term quality, evidence support, core function identification, and annotation action justification. Use for PR review comments, review follow-up automation, and QA of gene review YAML.

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。

Use this agent when you need to extract and summarize key findings from scientific references that are relevant to a gene's function. This agent should be used after references have been identified in a gene review to provide detailed supporting evidence from the literature. The agent will look up cached publications and extract only the most relevant findings related to the gene's direct function, excluding irrelevant experimental details unless they directly inform gene function.

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Evaluate and review GO-CAM (Gene Ontology Causal Activity Model) activities / annotons — molecular-function typing, has-input, causal relations, complexes, evidence — and check their consistency with gene annotation reviews. Use when reviewing cached GO-CAMs under gocams/, filling a GoCamReview YAML (gocams/<id>/<id>-review.yaml), or grounding a module in GO-CAM models.

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Fierce autonomous internal co-founder. Bounded web research for evidence-backed improvements. Structured idea formulation with self-critique filter that rejects ideas not serving the goal. Auto-implements high-confidence aligned improvements, proposes medium-confidence ideas for approval. Evaluates viral coefficient, AI search visibility (GEO), and solo SaaS economics. Considers higher pursuits: employing disabled people, spiritual tech investigation, 99% wealth donation ethos.

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QA-test a website or web app and return a 1-5 quality score (5 = flawless, 1 = broken) with evidence. Use when the user wants to test, QA, evaluate, score, or "check how good" a site, page, flow, or app — including a local dev server (e.g. "qa test localhost:5173", "does the checkout work?", "rate this landing page"). Drives a real Browser Use cloud browser, tunneling localhost automatically.

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Investigation flow (Glob -> Grep -> Read), evidence-based research with file:line references, structured output format for AI consumption. Use for pattern discovery, implementation research, and codebase investigation.

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General workflow for auditing ML CI failures, experiment regressions, training run failures, golden metric failures, and telemetry-backed ML work-product claims from local repositories, logs, metrics, configs, and artifacts. Use when Codex needs to decide whether an ML failure is a model/convergence issue, correctness bug, data/config issue, infrastructure/runtime issue, evaluation/gating policy issue, or unsupported claim, and produce structured evidence-backed outputs.

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Use SmokingGun to find complexity candidates and organize imported optimization evidence.

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Write or refresh evidence-grounded editorial summaries for stablecoin detail pages, including draining the AI-summary candidate queue after scoring changes.

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Curate evidence-backed collateralQuality and whole-book custodyModel labels. Use when adding a stablecoin or auditing Selector custody eligibility and DDR depeg-duration verdicts.

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Refresh tracked pre-launch stablecoin milestones, dates, launch phases, featured content, and promotion evidence. Use for the recurring upcoming-assets review.

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。

Research and populate tracked stablecoin compliance sidecars for the U.S. GENIUS Act, EU MiCA, or both. Use when adding or auditing authorization, applicability, pathway, or disclosure evidence.

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Use when curating, refreshing, expiring, calibrating, or equivalence-testing evidence and publication inputs for the active Safety Score model. Not for unrelated scoring models or copy-only changes.

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。

Drain the Pharos Dependency Map coverage-audit queues into evidence-refreshed edges, reviewed target dispositions, or documented deferrals. Use monthly after weekly production dependency audits, after dependency coverage drops, or when reviewing adapter gaps, material unlinked slices, symbol leads, duplicate/split groups, or unverifiable published edges.

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Research stablecoin reserve composition, review provenance, custody evidence, dependency edges, and backing-pillar slices; populate the owning reserves sidecar only when explicitly requested.

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。

Draft a short, prioritized questionnaire for a collaborating stablecoin team when public evidence cannot resolve important Pharos data or confidence gaps.

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。

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.

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。

Batch wrapper for /gaia-ingest. Ingests a bounded set of already-verified evidence rows through CLI-only writes, uses --no-build on every row, appraises Trust Magnitude for every affected named skill, then runs exactly one build and validation pass. Use for an L4-approved intake after /ev-pipeline; benchmark-result rows also require a Phase 2B report and explicit human gate approval.

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Fuse all of a contributor's named skills into a single fusion node (suite capstone) in the registry. Use when the user says "fuse <contributor>'s skills", "create a suite for <contributor>", "build a capstone for <user>", "fuse all of <user>'s named skills", "create a suite fusion", "consolidate <contributor> into one skill", or explicitly types /gaia-fuse-full-suite. Also triggers when a contributor has accumulated 3+ named skills and the user asks what to do next with them, or when someone asks "can we make a suite from these?". This skill: collects component IDs from registry/named/<contributor>/, verifies nodes exist, researches evidence and appraises Trust Magnitude, runs `gaia dev fuse` to write the fusion node and suite manifest, validates, and opens a PR on a review/meta/ branch.

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。

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.

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Review a Gaia curation PR or branch as a read-only merge gate. Use for canonical registry promotion, schema, evidence, prerequisite, nomenclature, installability, and generated-artifact checks. Route intake batches to /gaia-draft-curate and unrelated PRs to /review.

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。