「evidence」の検索結果

Draft, confirm, and synchronize research status, evidence, blockers, and review-ready GitHub summaries using the Research Memory skill, GitHub conventions, and file templates.

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Use when auditing an agent codebase against the 12-Factor Agents methodology, reviewing LLM-powered system architecture, or assessing agentic app compliance. Triggers on "analyze agent architecture", "12-factor audit", "how compliant is this agent", or "evaluate this LLM app". Also applies when comparing frameworks or planning agent improvements. Not for quick checklists — this performs deep per-factor codebase analysis with file-level evidence.

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Run an autonomous overnight campaign to find, prove, fix, and document CI flakes. Use when the user asks to stabilize CI through repeated full-pipeline runs and leave an evidence-backed draft PR.

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。

Provision and drive a `pu` box — an Incus container used as a clean Linux host for CI, builds, and evidence capture. Use when you need to run something on a fresh remote box instead of the user's machine: `nix run` a build, run CI against a real host, capture screenshots/video off-machine, or reproduce on a pristine environment. Covers create/connect/scp/destroy, running remote commands, copying artifacts back, and the no-egress failure mode. Triggers on "pu box", "spin up a box", "run this on a box", "ephemeral host", "pu create/connect/destroy".

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Run this repo's CI end-to-end — the kolu-specific procedure on top of the odu runner: the odu MCP front door, banned opt-out flags, linux-only platform pinning, venue-pool leasing, fail-fast surfacing, e2e timing evidence, and the green-gate. Triggers on "run CI", "drive CI", "re-run the pipeline", "close the red check", "warm the pool". Runner mechanics live in the `/odu` skill.

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Launch the kolu dev server on two RANDOM free ports so it never collides with the running production `kolu.service`, remember the ports for the rest of the session, and tear down only the dev instance. Load before running the app locally — for evidence capture, driving a live kolu with the chrome-devtools MCP, or any `just dev` you'd otherwise run by hand. Triggers on "run kolu locally", "launch the dev server", "boot kolu", "drive a live kolu", "start the app to screenshot it", or before pointing chrome-devtools at a local kolu.

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Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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Never tags, pushes, edits, or publishes. Read-only evidence pack and curated RIPDPI release notes from Git/GitHub history for a stable-tag-to-candidate-SHA range. Use when preparing a changelog or release notes.

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Direct substantial repository work across Claude Code, Codex CLI, or Grok Build with a concise brief, parallel agents, evidence-based completion, and optional cross-CLI continuation. Use for project onboarding, multi-step implementation, agent coordination, verification planning, low-interruption setup, or deciding how another CLI should take over. Do not use it as a permission gate or mandatory workflow.

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Continue a task in Claude Code through a portable Director handoff packet. Use when work started in Codex CLI or Grok Build should move to Claude, or when a fresh Claude session needs the current decisions and verification evidence.

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Quellenbasierte Profile einzelner Wettbewerber aus öffentlichen Informationen erstellen. Nutze diesen Skill, wenn Positionierung, Zielgruppe, Produkt, Preise, Organisation und Belegbehauptungen eines Anbieters zusammengetragen werden sollen, als Kurzbrief, fokussiertes Profil oder vertiefte Recherche. Trennt Tatsache, Anbieterangabe, Schätzung und Hypothese in einem Claim-Ledger, hält Quellen mit Datum fest und beachtet Datenschutz, Datenbankrechte, Urheberrecht und Geschäftsgeheimnisse. Kein Scraping über das Freigegebene hinaus, keine Personendossiers. Für vergleichende Seiten: competitors.

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Audit the reasoning of a document or argument (memo, proposal, investment analysis, board paper, article, the user's own draft): claims, evidence, unstated assumptions, logical gaps, fallacies, and what would falsify it, each anchored to quoted text. Use whenever the user wants reasoning examined, in any language ("audit this argument", "is this analysis sound", "poke holes in this proposal", "review the logic of my draft"; Vietnamese "phản biện giúp tôi", "soi lập luận này", "tài liệu này có lỗ hổng gì", "góp ý bản nháp của tôi"), even when they never say "critical thinking". Also use when the user drops a document and asks whether to trust or act on it, or asks to see their reasoning profile. Not for company-level strategic bets (strategy-board) or learning a topic through dialogue (socratic-questor).

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Verification before completion claims. Use when about to say "done", "fixed", or "complete". Runs checklist by workflow type with evidence requirements.

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USAP agent skill for Cyber Insurance. Assess cyber insurance coverage adequacy, identify coverage gaps, maintain claim-readiness evidence, and support renewal applications.

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Verifies provider credentials via NPI MCP, searches Medicare coverage policies via CMS Coverage MCP, and maps clinical evidence to policy criteria with MET/NOT_MET/INSUFFICIENT assessment, per-criterion confidence scoring, and documentation gap analysis.

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SEO audit and keyword strategy — investigate a site's real search opportunities, shortlist candidates, and recommend the one to three changes most likely to grow organic traffic that converts. Evidence-first — metrics come from a tool or are written as unknown. Use when asked to "improve our SEO", "do keyword research", "audit our SEO", "why aren't we ranking", or "what should we fix first for search".

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Design a compromise assessment — hunting scope, methodology, and evidence collection. Use when asked "are we compromised", "run a compromise assessment", or "scope a threat hunt".

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Expert 5-dimension design critique — philosophical, scored, actionable. Use when asked to "critique this design", "expert review", "score my design", "how does this look", "is this good design", "design feedback", or "review this UI". Different from /form-audit (which is technical QA for consistency/compliance) — form-critique evaluates design as a craft object: philosophy, hierarchy, execution, function, and innovation each scored 0–10 with a punch list. Add "as a report" or "give me a visual report" to produce an HTML file with SVG radar chart, evidence cards, and Keep/Fix/Quick-wins action lists — useful for design reviews and stakeholder presentations instead of CLI output.

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Expert guide for autonomous deep research, iterative web search, citation verification, evidence graph synthesis, and hallucination mitigation / Panduan ahli riset mendalam otonom, pencarian web iteratif, verifikasi sitasi, dan mitigasi halusinasi.

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Identifying species in the field using dichotomous keys, gestalt recognition, diagnostic features, and habitat context. Covers the working identification protocol from first encounter through confidence-rated record, the vocabulary of field marks, the discipline of negative evidence, and the honest reporting of uncertain IDs. Use when the task is to name a living organism encountered in the field.

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Field observation, data collection, and research methods for geographic inquiry. Covers site selection and sampling strategies, field observation techniques (landscape reading, transects, quadrats), survey and interview methods for human geography, GPS and field mapping, environmental monitoring and instrumentation, data recording and field notebooks, ethical considerations in fieldwork, and the integration of field data with GIS analysis. Use when planning geographic field research, designing data collection protocols, evaluating field evidence, or connecting field observations to broader geographic analysis.

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Recognition and mitigation of systematic reasoning errors documented in the heuristics and biases tradition. Covers confirmation bias, availability, anchoring, representativeness, framing effects, hindsight bias, overconfidence, and motivated reasoning. Each bias is presented with its mechanism, diagnostic signal, and structured mitigation. Use when you suspect your own or another reasoner's conclusions may be shaped by systematic cognitive distortion rather than evidence.

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Use the moment a request is underspecified and you are about to act on an ASSUMED goal. Enumerate the candidate goals the request could mean, project the action or artifact each one implies, and check whether they diverge: if two or more plausible goals lead to materially different actions or artifacts, ask exactly ONE targeted clarifying question; otherwise proceed on the most-likely goal and state the assumption in one line. Clarification is an evidence-producing action, not a delay — but one question, never an interrogation. Distinct from gsd-spec-phase (GSD-phase-bound, emits a heavy SPEC.md) and intent-router (fetch strategy, not goal disambiguation). Backed by agent goal-state inference (arxiv 2606.16813v1). Triggers on acting under an assumed goal when the request admits more than one materially different reading.

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Pick among candidate outputs (code, configs, plans) by running them on diverse inputs and clustering by behavioural fingerprint, rather than by textual aggregation or log-probability. Activates when an executor returns multiple plausible candidates that need disambiguation, when output-majority voting would be the default choice, or when reviewing generated code that has not yet been validated. The 2026 evidence (Semantic Voting, arxiv 2605.08680v1) is that any execution-based selector dominates output-majority voting by 19-52pp; sketch-generated inputs beat random fuzz by 11.3pp. Triggers: "pick the best candidate", "majority vote on code", "select from N samples", "validate the generated output", "behavioural verification".

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。