「evidence」の検索結果

Run the Anabasis v2 improvement loop, the Super Loop: find the one link that holds the climb, choose one change against it, prove its path, put a prediction on record, launch, watch, read the log, decide the next move. Use when the operator asks to keep a campaign going, to run a pass of the loop, what to launch next, why a campaign is not climbing, or what a finished round means for the next one. Owns the choice of experiment and the reading of its evidence; the operator owns promotion, a freeze, a stop, spend and the solve's condition.

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Quality validation specialist covering functional, performance, and security testing to ensure production readiness through evidence-based testing.

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 for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

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Maintain the pure-Go SQLite password identity store, reusable parser, immutable account evidence, idempotent enrollment, portal injection, and login E2E tests. Excludes local JSON database internals and MFA/profile feature implementation.

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Audit AuthCrunch security boundaries, triage vulnerability reports and scanner findings, reproduce authentication or authorization failures, and prepare evidence-backed remediation. Covers trust, credentials, redirects, concurrency, diagnostic logging, and dependency exposure.

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Maintain optional cross-device portal login, its directive parser, QR and polling UI, approving-browser binding, single-use transfers, MFA and provider evidence, logout invalidation, and TLS/browser tests.

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Maintain refresh-token login evidence, MFA completion, sandbox redemption, immutable local identity, credential-version invalidation, transactional current-identity checks, and captured upstream provider snapshots in AuthCrunch.

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Distill a provided document into a flat, importance-ranked list of its key points, each with a salience rank, a rationale, and a verbatim line-cited evidence snippet. Use when the user wants to "distill", "summarize the key points", or "extract the essence" of a document or pasted text.

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Builds, revises, restyles, and critiques deliberate, editable Feishu / Lark whiteboards from content, references, existing SVGs, or live boards. Use for whiteboards, infographics, diagrams, system maps, timelines, decision boards, posters, and visual explainers that need factual fidelity, strong hierarchy, intentional composition, and evidence-based review rather than a generic grid of equal cards. Routes creation, revision, and critique through separate playbooks; commits to a content-and-design contract before drawing; validates deterministic SVG defects; renders and inspects the actual artifact; and uses an independent final reviewer for material deliveries.

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 when asked to map or analyze flows, pipelines, processes, or sequences of events in this repo — e.g. "mapa el flujo", "flow", "pipeline", "ciclo de vida", "trace the request", "how does the build/release flow work", "diagrama del flujo". Maps data flows, request lifecycles, CI/CD pipelines, and state transitions with verified file:line evidence. Distinct from analyze-code (which maps code structure); this skill maps movement over time.

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Portable Codebase Argus agent playbook for evidence-first multi-agent review of GitHub pull requests, CI failures, GitHub Actions logs, GitHub App webhook review, /argus PR comment commands, autofix branch planning, OpenAI/Claude/Gemini/Codex provider tribunals, downstream merge/rebase work, and long-lived fork sync against an upstream repository.

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Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only.

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Build and operate a complete, brand-neutral Reddit intelligence system with approved read-only monitoring, grouped keyword rules, evidence-backed AI scoring, a persistent opportunity bank, dashboard review, urgent-alert and weekly-digest previews, content briefs, and human-only response drafts. Use for "reddit intelligence", "reddit monitor", "reddit listener", "watch subreddits", "find reddit opportunities", "content ideas from reddit", "community listening", or setting up this workflow for a client or brand.

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Build and maintain a provenance-clean proof library — inventory every real proof asset (analytics, reviews, permitted testimonials, case studies, press, certifications), categorize it, rewrite each cleared item in 3 lengths, fuse top assets with narrative, and gate everything through FTC testimonial rules before it can ship. Use when "proof library", "gather our proof", "authority builder", "collect testimonials", "social proof assets", "proof points for the sales page", "what results can we claim", or any request to assemble evidence for marketing claims. NEVER invents proof — missing proof is reported as a gap.

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Multi-platform brand intelligence pulse - collect cited public reputation evidence across web, news, YouTube, X, LinkedIn, Reddit, and review sites, then turn it into objection mining, content angles, competitor positioning, and surround-sound actions. Use when "brand monitor", "brand pulse", "what are people saying about us", "multi-platform reputation", "brand intelligence", "weekly brand monitoring", "objection mining", or "public reputation scan".

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Evidence-first marketing audit of a third-party local business (café, roaster, shop, restaurant, hotel, clinic, home service) from a Google Maps, share.google or website link — located DataForSEO rankings, map packs, search volume and seasonality, listings, reviews, backlinks, AI-assistant answers and a site crawl, plus direct checks (real-browser access, page weight, store shipping quotes, email DNS, mobile screenshots) — delivered as an owner-facing report with priced offers, an exact change list and a 12-week plan, optionally localized and bilingual. Use when "audit this business", "full marketing audit of <business>", "prospect audit", "local business audit", "use DataForSEO for the hard SEO data", "go deeper", "rerun it for local <market>", "also in Spanish", "give me the offers, changes and 3 month plan", or a business link arrives with "audit". For auditing your own product across channels use /kai-audit.

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Use when 高教社杯/CUMCM mathematical modeling work needs lightweight reusable paper assets, national-prize style paragraph templates, section controls, per-question code/plot/test scaffolds, evidence registries, paper fragments, reproduction scripts, or safe reuse of prior contest project structure without copying old problem-specific content.

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。

Reverse-engineer a supplied video into a shot-by-shot generation specification, displayed evidence frames, and paired Chinese-English prompt packages. Use for requests such as 视频反推提示词, 视频转提示词, 从视频生成提示词, 视频逆向提示词, 逐镜头反推, 分镜拆解并生成提示词, 反推视频 prompt, or video-to-prompt; also use for Veo, Sora, Kling, Wan, generic prompt adaptation, and bounded generate-compare-optimize loops. Do not use for ordinary video summaries or basic transcription.

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。

Plan changes to this repository using its domain CLI, MCP boundaries, and harness validation evidence.

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。

Evaluate proposed repository harness changes with pinned Darwin tools and explicit evidence limits.

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。

Evaluate proposed repository harness changes with pinned Darwin tools and explicit evidence limits.

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。

Plan changes to this repository using its domain CLI, MCP boundaries, and harness validation evidence.

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。

Default entrypoint and master ctf-sandbox-orchestrator workflow for CTF, exploit, reverse engineering, DFIR, pwnable, crypto, stego, mobile, AI-agent, cloud, container, Active Directory, Windows-host, and identity challenges. Use first when the user presents challenge infrastructure, binaries, prompts, hosts, or identities that should be treated as sandbox-internal by default and Codex needs to choose, route, and load the right downstream analysis path with concise evidence.

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for enterprise mail abuse, OAuth consent, inbox or forwarding rules, transport rules, shared mailbox access, phishing chains, and token-to-mailbox side effects. Use when the user asks to trace mailbox rules, OAuth consent grants, forwarding or delegate abuse, shared mailbox access, message-trace evidence, or explain how mail artifacts turn into persistence, exfiltration, or privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。