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Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.

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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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Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).

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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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Build/test/lint verification pass for this Flutter app — runs codegen, analyze, test, then iOS + Android native builds in parallel, then `dart format`. Does NOT commit anything; leaves the working tree dirty so the user can review and commit on demand. Used at the end of the prd → techspec → tasks → implement-tasks-sequence flow before `pr-review`, and can also be invoked manually when the user says "verify build", "run full verification", or "check everything".

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Use when testing PyQt/PySide6 applications with pytest-qt - qtbot fixture, signal/wait patterns, mouse/keyboard simulation, dialog testing, model/view testing, threaded code testing, or manual debugging techniques

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Sync processed CSS design tokens with JavaScript theme objects for React Native. Use when aligning tokens after Figma sync, checking token consistency, or updating JS theme files manually.

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Manually trigger artifact regeneration, versioning, and chore commit. Use when you need fine-grained control over when registry artifacts sync (outside the automated sync-artifacts.yml workflow).

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Reference guide for the full manual Gaia curation pipeline. Invoke at any phase when unsure what command to type next: gaia-curate, L4 review, gaia push, ev-pipeline (Phases 0–4), gaia-ingest, or close. Trigger phrases: "/gaia-consult", "what's the command for", "remind me how to", "I'm lost in the pipeline", "what do I do next", "consult the pipeline doc", "pipeline reference".

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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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Burn timed, styled captions into a finished video on the local machine, without re-rendering the source. This is the manual fallback to the API's captioning endpoint, POST /v1/captions, which stays the default path: come here when the style the user wants is outside the API's presets, when the wording has to be hand-corrected before it is burned into the pixels, or when the source was rendered with audio disabled and the API refuses it. Transcribes the audio with Whisper, groups words into reading phrases, renders the captions in a real browser via HyperFrames, and composites them over the source with ffmpeg using a real alpha channel. Use when the user has an MP4 with speech and asks to add captions, subtitles, burned-in text, TikTok-style captions or word-by-word text to it, and the API path has been ruled out. Runs out of band, so it costs no credits and works on any video file whoever generated it. Not for generating video (use the video skills) and not for a separate .srt/.vtt sidecar file.

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Identifies and unpacks packed binaries: detecting packers from section names and entropy, automatically unpacking UPX, and manually unpacking custom packers by finding the OEP and dumping. Activates for requests to unpack a packed sample, detect a packer, or recover the original binary from UPX or a custom packer.

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Turn a moment of friction — a conflicting PR, a wedged runner, a mysterious red check, a repeated manual chore — into a durable, actionable report. Sizes up the scenario, captures the evidence, separates one-off from SYSTEMIC, proposes a fix, and routes it (fix now, or hand off). Reports are LIVING documents that the fixing agent updates with the outcome. Invoke whenever something feels like it shouldn't have been this hard, or when the same annoyance shows up twice.

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Place pre-screened literature citations into a LaTeX or Word manuscript, or restyle the citations already in one. Three modes: (1) inline placement — inline \cite{}/\citet{}/\citep{} with a compiled references.bib, for author-date journals (APA, MLA, Harvard, Chicago author-date, IEEE, Vancouver); (2) footnote placement — full formatted \footnote{} or OOXML footnotes for legal and notes styles (Bluebook, OSCOLA, Chicago, APA, McGill) with Id./supra short forms; (3) restyle — convert existing footnote citations from one style to another. This skill is manual-invoke ONLY — trigger ONLY when the user explicitly runs /cite-placement or explicitly names the "cite-placement" skill. Do NOT auto-trigger on general citation, footnote, or reference requests.

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N-round adversarial review pipeline for empirical research output — the chain from data to LaTeX tables to a manuscript that cites them. A Claude drafter proposes minimal diffs, a deterministic mechanical battery gates every diff from a clean state with a regression gate, a Codex reviewer files check-backed critiques, and a blind judge panel decides residual disputes. Manual-invoke ONLY: trigger when the user explicitly runs /adversarial-empirical-review or names 'adversarial-empirical-review' / 'adversarial empirical review'. Do NOT auto-trigger on generic 'review my results', 'check my tables', or manuscript-editing requests. For prose-style refinement use style-emulation instead; this skill AUDITS WHETHER THE TABLES ARE CORRECT — that each number in the tables is what the analysis code computes, reproduces from the data, and is internally consistent. It is an empirical + code review: the manuscript is read only to resolve table numbering, and prose is not examined.

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Run the critical path smoke test gate before QA hand-off. Executes the automated test suite, verifies core functionality, and produces a PASS/FAIL report. Run after a sprint's stories are implemented and before manual QA begins. A failed smoke check means the build is not ready for QA.

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Quality review of test files and manual evidence documents. Goes beyond existence checks — evaluates assertion coverage, edge case handling, naming conventions, and evidence completeness. Produces ADEQUATE/INCOMPLETE/MISSING verdict per story. Run before QA sign-off or on demand.

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Orchestrate the QA team through a full testing cycle. Coordinates qa-lead (strategy + test plan) and qa-tester (test case writing + bug reporting) to produce a complete QA package for a sprint or feature. Covers: test plan generation, test case writing, smoke check gate, manual QA execution, and sign-off report.

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Generate a QA test plan for a sprint or feature. Reads GDDs and story files, classifies stories by test type (Logic/Integration/Visual/UI), and produces a structured test plan covering automated tests required, manual test cases, smoke test scope, and playtest sign-off requirements. Run before sprint begins or when starting a major feature.

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Use when safely removing dead frontend code, unused exports, stale components, obsolete routes, unused dependencies, or cleanup targets found by tools such as knip, depcheck, ts-prune, TypeScript, ESLint, or manual review. Do not use for feature rewrites that change behavior; Chinese triggers include dead code, clean up unused, refactor clean, dependency cleanup, delete useless code.

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Creates feature branches with optimized short naming, auto-incrementing, and commit type detection (feat/fix/refactor). Supports manual descriptions and auto-generation from uncommitted git changes. Use when user requests to create branch, start new branch, make branch, checkout new branch, switch branch, new task, start working on, begin work on feature, begin feature, create feature branch, run /create-branch command, or mentions "branch", "feature", "new feature", "feat", "fix", or "checkout".

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Creates isolated git worktrees in .claude/worktrees/ with intelligent branch naming, auto-incrementing, and commit type detection (feat/fix/refactor). Supports manual descriptions and auto-generation from uncommitted git changes. Use when user requests to create worktree, start isolated work, parallel development, run /worktree command, or mentions "worktree".

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Deletes merged git branches (local and remote) and flags stale unmerged branches for manual review. Use when user mentions "cleanup branches", "delete merged branches", "prune old branches", "remove stale branches", "branch cleanup", or runs /cleanup-branches command.

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Run the full speckit workflow end-to-end — specify, plan, critique, tasks, implement, review — making all decisions autonomously. Stops before extract; run that manually.

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。