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概要と使いどころ
Use when asked to test a Lumen change against consumer repos before releasing it: a breaking or architectural change, a lint-plugin upgrade, peer/prod dependency moves, build or packaging changes, or to check how consumers use a component, prop or variant. Runs the change (or a usage scan) across the production consumers in the adoption registry and outputs a shareable HTML report.
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 how other design systems handle a component, prop, token or pattern; to name a component, prop or token; to research best practices (composition, when to split, a11y, responsiveness, motion) before building; or for a design-system discovery or benchmark report. Compares Coinbase CDS, Adobe Spectrum, Astryx, Material, Primer, MetaMask DS and Base UI, anchors the recommendation in Lumen's code, and outputs a shareable HTML report.
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。
Produce the monthly "Stablecoin Pulse" 2-page PDF for a partner team (default Polaris) from Pharos API data plus X and web research, explaining why supply, chains, and pegs moved. Use at month end or when asked for a monthly stablecoin trends/pulse report; not for the daily digest or Telegram pulse.
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。
Generate a NullPointer Studio styled PDF penetration test report from findings.json. Produces a professional dark-themed PDF with executive summary, risk dashboard, per-finding cards with business risk, remediation summary, and clean controls section.
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 the H1 Brain MCP Server to pull HackerOne program policies, scope definitions, and disclosed vulnerability reports directly into Claude's context. Based on Critical Thinking Bug Bounty Podcast Episode 166.
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。
Implement the 5-stage Funnel workflow (Notes → Leads → Primitives → Findings → Reports) for structured bug bounty hunting. Based on Critical Thinking Bug Bounty Podcast Episode 166.
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。
Triage the Gaia issue backlog and skill-batch intake queue. Use this skill when someone asks to: "triage issues", "clean up the issue tracker", "review the backlog", "close stale issues", "process the intake queue", "review skill-batches", "evaluate draft skill proposals", "approve or reject pending skills", "is this issue still valid?", "what's clogging the backlog?", "run a triage pass", or /gaia-triage. Covers two workstreams: (1) GitHub issue lifecycle — identifying resolved, stale, or need-more-info issues and acting on them via gh CLI; (2) skill-batch intake — evaluating draft proposals in registry-for-review/skill-batches/ and routing them toward promotion or rejection. This is the gatekeeping step before new skills enter the canonical registry; and (3) a cross-repo triage sweep — sizing, P0-P4 prioritization, umbrella/epic synthesis, and assignment across every gaia-research org repo, on the one headquarters tracker.
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 skill when the user wants to turn code graph analysis into tracked GitHub issues — "audit the architecture", "find god nodes", "triage architectural debt", "run graphify and log issues", "what's over-coupled in this codebase", "create issues from graphify findings", "check for structural problems", "scan for architectural smells", or any request that combines codebase topology analysis with issue tracking. This skill runs graphify to build a dependency graph, parses GRAPH_REPORT.md for god nodes and structural patterns, converts findings into GitHub issue payloads, and optionally pushes them to the repo. It bridges static analysis and project management in a single automated pass. Requires graphify and gh CLI.
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。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
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。
Append a session/state snapshot to MEMORY.md (regardless of where it lives — for this repo it's `founder/MEMORY.md`). Use when the user says "snapshot memory", "save state to memory", "/memory-snapshot", "log what happened in MEMORY", or otherwise asks to record the current session's outcomes for the next orchestrator. Locates the project's MEMORY.md, prepends a dated entry above the previous snapshot (newest first), preserves every existing entry (NEVER overwrites or truncates), and reports back the file path + byte delta. Not for one-off feedback memories (use the user-level memory system at ~/.claude/.../memory/ for those). Not for trimming or deleting old entries.
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。
Regenerate and commit Class S site-served artifacts after registry changes, then sync documentation across the main repo and the adjacent wiki. Use this skill when: you've changed registry/nodes/, registry/named/, or named-skills.json and need to regenerate docs/graph/* so the live website reflects the update; CI Guard E (docs-cohesion.yml) is failing because Class S artifacts are out of date; someone says "sync the docs", "regenerate docs", "run gaia dev docs", "update the site graph", "commit the Class S artifacts", "website is stale", or "update the wiki"; or you're finishing a registry PR and need to ensure docs/graph/gaia.json, docs/graph/gaia.gexf, docs/graph/gaia.svg, and docs/graph/named/index.json are committed alongside the source change. Also covers updating README.md, docs/index.html, and mirroring changes to the adjacent wiki repo at ../gaia-wiki.
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。
Measure CI churn cost for a pull request: how many commits and how many CI-compute seconds were burned on avoidable "fix the CI" push rounds. Use when you want to understand the efficiency cost of a PR's iteration cycle, get actionable pre-push check suggestions, or include a churn summary in a pipeline report. Triggers: "ci churn", "how much CI did we burn", "avoidable commits", "ci efficiency", "wasted CI time", "churn report", "/ci-churn". Called automatically by /fp-drift at pipeline close.
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。
Client reporting, quality assurance, and financial operations management. Handles KPI frameworks, compliance audits, budget tracking, and launch checklists. Use when: managing client dashboards, ensuring brand compliance, conducting QA reviews, tracking marketing spend, ensuring GDPR/CAN-SPAM compliance, handling a request to delete someone's data across the marketing stack, deciding whether an AI voice or AI presenter has to be disclosed, proofreading deliverables. Also triggers on: client reporting, QA, quality assurance, brand compliance, marketing budget, financial tracking, legal compliance, GDPR, CAN-SPAM, proofreading, launch checklist, right to erasure, right to be forgotten, data deletion request, DSAR, someone asked us to delete their data, do we delete or suppress, suppression list, they unsubscribed and we emailed them again, we deleted them and they came back, restored a backup and re-emailed people, custom audience still has deleted contacts, California Delete Act, DROP, data broker deletion, enrichment records disappearing
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。
Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, creative concept diversity for Meta Advantage+ (why six variants of one ad are not a diverse library, and what to brief instead), creator-made ad creative on a spend-share deal, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.
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。
Code review by several models at once — Claude sub-agents, OpenAI Codex, and a cheap third reviewer via OpenCode — reconciled into one report. Reviews whatever is named: a diff, a branch, specific files, one function, a legacy module, a whole repo. Use for any review request, a second or third opinion, a cross-check before a PR, or "code-review", "multi", "consensus 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。
Continuously monitor a GitHub PR for merge conflicts, CI failures, and CodeRabbit review comments, then automatically fix any issues found. Polls every 5 minutes and loops until every check is green. Use this skill whenever a PR has just been created or code has been pushed to a PR branch — it should be the default follow-up action after any PR creation or push. Also trigger on: "watch this PR", "guard this PR", "monitor CI", "keep fixing until green", "PRを監視して", "CIが通るまで 直して", /pr-guardian. When a PostToolUse hook reports that a push or PR creation just happened, proactively invoke this skill to start monitoring without waiting for the user to ask.
This skill enables GitHub repository documentation exploration using DeepWiki API directly via curl. Use when researching repository structure, understanding library APIs, or asking questions about open-source projects. MCP server not required.
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。
Extracts indicators of compromise from raw analysis artifacts: parsing strings dumps, sandbox reports, PCAP summaries, and logs for URLs, domains, IPs, hashes, mutexes, and file paths, then deduplicating and typing them. Activates for requests to extract IOCs from analysis output, pull indicators from a report, or harvest atomic indicators.
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。
Uses capa to identify malware capabilities from a binary: running rule-based detection over disassembly, mapping matched capabilities to MITRE ATT&CK and MBC, and interpreting results to focus deeper analysis. Activates for requests to run capa, generate a capability report, or map a sample's behaviors to ATT&CK automatically.
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。
Establishes a disciplined malware sample repository: content-addressed storage by hash, encrypted/password-protected archiving, consistent metadata records, and chain-of-custody tracking so samples are reproducible and safe to handle. Activates for requests to organize a malware repository, manage samples, or track sample metadata and provenance.
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。
Prepares indicators of compromise for safe sharing: defanging URLs, domains, IPs, and emails so they cannot be accidentally clicked or resolved, and formatting them into STIX/CSV/MISP-friendly output. Activates for requests to defang IOCs, sanitize indicators for a report, or export indicators for sharing.
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。
Stand up a fast, cached, isolated, disposable macOS CI lane on Tart — layered golden VM images, ephemeral per-job GitHub Actions runners, host-mounted caches, and a reusable per-repo vm-image manifest. Use when setting up VM-based CI for Pulp or generalizing it to another repo, building/refreshing golden images, wiring ephemeral runners, or debugging the VM lane.
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。
Route repository-qualified changes across Pulp and Vellum using Pulp's exact ownership projection. Use when a change touches design import, Chromium authoring, DesignIR, visual harness, screenshot, Skia/Dawn, runtime assets, or another path represented by `.github/vellum-ownership.json`; when deciding whether work originates in Pulp or Vellum; or when validating the cross-repository routing contract.
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。
Maintainer side of an outside contribution — find what has arrived (fork PR, issue, or patches sent out-of-band), adopt it into an in-repo branch with authorship intact, review it against the repo's bar, and ship it through the normal merge path. Use when landing work from someone without write access or without the CI fleet.
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。