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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so the live website reflects the update; CI Guard E (docs-cohesion.yml) is failing because Class S artifacts are out of date; someone says "sync the docs", "regenerate docs", "run gaia dev docs", "update the site graph", "commit the Class S artifacts", "website is stale", or "update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.

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Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.

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Use this skill whenever the user wants to see how their branch will look on the live Gaia website before merging — "preview this branch", "show me what this looks like", "deploy a preview", "trigger a design preview", "can I see the site with these changes", "preview the skill profile", "check how this renders on the site", "spin up a preview deployment". This skill dispatches a Cloudflare Worker preview deployment for the current branch via GitHub Actions — no local build tooling required. Ideal for containerized environments, design reviews, and confirming that newly curated skills or profile pages render correctly before a PR is merged to main. The preview does NOT regenerate docs; it deploys `docs/` from the branch as-is. If your change depends on regenerated Class S artifacts, run `gaia dev docs` and commit those first — the preview then reflects them.

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 this skill for Phase 3 of the evidence verification pipeline — the adversarial audit step. Use when you need to check the evidence data lake for bad data before ingestion: dead links, wrong URL formats (tree/ vs blob/), subjective wording ("elite", "high-quality"), stale migration notes, benchmark catalog misuse/vendor-claim leakage, or skills whose star evidence conflicts with classified evidence level. Triggers on phrases like: "audit the data lake", "adversarial check", "ev-adversarial-audit", "check for noise in evidence", "flag bad evidence", "run the audit phase", "quality check the by-type files", or any reference to Phase 3 of the pipeline.

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 rendered evidence a human-gated frontend PR owes its reviewer: capture each changed surface (plus the before state for anything modified, plus mobile width), then generate one self-contained local HTML page the founder can open and review without checking anything out. Use when a PR is gated by the "Frontend changes are HUMAN-GATED" section of CLAUDE.md, or when the user says "/design-gate", "screenshot evidence for this PR", "prep this for founder review", "build the design evidence page", "what does this look like before and after". The page comes from a template script, not hand-written markup. Output is session-local and never committed. Do NOT use for non-gated changes: typo/grammar/factual fixes in an unchanged block, dead link targets, alt/ARIA fixes with no visual change, cache-bust bumps, or refactors with no rendered diff.

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Top-level orchestrator for the Gaia Skill Tree evidence verification pipeline. Run this when you want to do a full evidence pass — collecting raw sources, verifying live GitHub star counts, running Phase 2B benchmark-source verification, adversarially auditing for quality/formatting issues, and checking that every URL is reachable — all in one coordinated sequence. Trigger phrases: "run the evidence pipeline", "full evidence pass", "verify evidence", "evidence verification pipeline", "run ev-pipeline", "check all evidence", "audit the data lake", "evidence quality sweep", "refresh evidence", "validate evidence sources". Also aliased as /evidence-verification-pipeline. Use the individual sub-skills (ev-collection, ev-star-verification, ev-adversarial-audit, ev-link-validation) only when you need to re-run one phase in isolation; for end-to-end work, always start 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。

Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.

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Build e-commerce storefronts: product catalog, cart, checkout, payments, and post-purchase flows. Use for online stores and marketplaces.

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。

Idiomatic modern C#: nullable reference types, records, async/await, LINQ, and .NET project structure. Use when writing, reviewing, or structuring C# applications.

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。

Read, write, and debug cron expressions with field reference, scheduling logic, and common patterns.

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。

Get productive with agentic coding assistants — task framing, iterative prompting, file-scoped workflows, review loops, and multi-file refactors. Use when pairing with an AI coding agent on real codebases.

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。

Write readable, maintainable code: naming, small functions, clear control flow, and honest abstractions. Use when writing new code, refactoring, or reviewing for readability.

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。

Precision position measurement — proper motions, parallaxes, reference frames, and working with Gaia data.

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。

A pattern catalog for autonomous agents — ReAct, plan-and-execute, reflection, multi-agent debate, toolformer-style tool use, and when each fits. Use when choosing the control pattern for an agent task.

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。

Design memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.

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。

Craft effective AI image prompts with structured syntax, style control, and iterative refinement techniques.

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。

End-to-end SEO operations for B2B SaaS organic visibility. Use this skill when you need keyword research, technical SEO audits, content optimization, link building strategy, international expansion, AI/AEO optimization, schema markup, Core Web Vitals improvements, and organic traffic growth planning. Also triggers on: SEO, keyword research, can we rank for this keyword, which keywords are actually worth it, qualify these keywords, check the SERPs, keyword shortlist, too many keywords, technical SEO, link building, content optimization, international SEO, hreflang, x-default, multilingual site, translated pages not ranking, our German site gets no traffic, language switcher, auto-redirect by country, machine translation SEO, content parity, ccTLD vs subfolder, AI search, AEO, GEO, Core Web Vitals, schema markup, organic traffic, G2 listing, Capterra, TrustRadius, review-platform category page, best software roundup, listicle placement, directory submissions, do we need a Google Business Profile in [country], local SEO with no office, Google Business Profile eligibility, virtual office address SEO, coworking address business profile, business profile suspended, NAP consistency, local citations for SaaS, LocalBusiness schema, server log analysis, log file analysis, what is Googlebot crawling, is Googlebot hitting errors, verify Googlebot, fake Googlebot, crawl budget, do we have a crawl budget problem, Crawl Stats report, new pages not getting crawled.

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Partner, channel, and ecosystem marketing for B2B SaaS — and the design of the partner program itself. Use this skill for co-marketing with technology alliances and channel partners, integration launches, joint campaigns and content, partner tiering and enablement, cloud-marketplace go-to-market (AWS, Azure, GCP listings, private offers, committed-spend drawdown), and for channel program architecture: whether to launch a partner program at all, which motions to run (referral, technology, services/SI, reseller), partner unit economics, margin and SPIF design, partner recruitment and certification ramp, and the rules of engagement that settle a contested deal. Also triggers on: partner marketing, co-marketing, channel, reseller, VAR, MSP, distributor, OEM, alliance, ecosystem, integration launch, marketplace listing, AWS Marketplace, private offer, MDF, joint webinar, co-branded, channel conflict, rules of engagement, deal registration, partner program design, should we build a partner program, partner economics, partner P&L, partner CAC, margin stacking, SPIF, rebate, partner recruitment, partner onboarding, partner certification, partner tiers, our partners signed up and never sold anything.

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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。

Execute a project from a folder of raw materials. Use when the user drops messages, screenshots, documents, drafts, and references into a project directory and wants Codex to identify the real goal, build a plan, do the work, drive the project to a submission-ready state, verify completion, and return a clear final summary of what was required, what was completed, and how it was done.

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Replace sentence-by-sentence revised or paraphrased text back into an original paper or document while preserving the original formatting, typography, paragraph settings, citation layout, and document conventions as the source of truth. Use when the user provides revised text that maps back to original sentences, paragraphs, sections, or the whole document, but may also contain clear local sentence merges or splits, and asks to replace it back into the source, keep the original formatting, do sentence-by-sentence replacement, preserve original formatting, or only swap wording without rewriting the document. Only allow minimal edits to the rewritten text when fixing citation formatting, restoring protected original content, restoring the original person reference, or minimally splitting/merging text back into original sentence slots; otherwise do not improve grammar, style, logic, or wording.

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。

Strip workflow notes, engineering meta text, status remarks, workspace references, and other process-facing language from any final deliverable such as a PPT, DOCX, PDF, report, manuscript, or submission package. Use when preparing a final export, submission-ready artifact, or client-facing handoff.

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。

Design, review, and improve Claude/Codex skills based on Anthropic's "The Complete Guide to Building Skills for Claude". Use when creating a new skill, rewriting SKILL.md frontmatter and workflows, fixing under-triggering or over-triggering, designing scripts/references/assets, building test cases, or preparing a skill for upload/distribution.

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Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise. This skill should be used when code-quality checks pass but the code would benefit from structural cleanup — deduplication, branching simplification, naming improvements, or dead-code removal. Invoked as a subagent from /code-quality or directly via the Task tool.

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。