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概要と使いどころ
Investigation flow (Glob -> Grep -> Read), evidence-based research with file:line references, structured output format for AI consumption. Use for pattern discovery, implementation research, and codebase investigation.
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 whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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。
Broad, pre-curation evidence reconnaissance for a declared Gaia skill, intake batch, upstream repository, or proposed generic capability. Run before choosing a discovery strategy or mapping topology, to give the curator independent research leads and counterevidence. Context only: never scores, grades, ratifies, ingests, or mutates the registry. Later ev-discovery and ev-pipeline phases validate/promote any selected leads.
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。
Consult this skill BEFORE proposing a fix to any CLI gap or schema gap that touches evidence, trust magnitude, evidence types, evidence grades, the TM formula, or star-level promotion gates. Also read it whenever an issue mentions citations, stars, commits, contributors, views, reviewers, percentile, arxiv, github-stars-own, repo-own, social-signal, benchmark-result, peer-review, self-attestation, fusion-recipe, verifier-attestation, or proxy-containment — those are the 10 canonical evidence types and the raw inputs that feed their formulas. Also read it when asked whether a skill qualifies for a given star level (0★–6★): the Star Bar and promotion gates live in `META.md`, not in the TM methodology page. Reading both prevents proposing a calibration that satisfies the TM grade threshold but violates a Star Bar installability or link requirement.
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。
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。
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。
Post-review intake closing skill. After an intake is resolved (whether accepted via review/meta PR merge or rejected/deferred at triage/evidence review), run this skill to post standardized, personalized closing comments on the PR (if any) and each intake issue. Comments include: evidence pipeline findings with /trust-appraise TM output, per-row artifact scores, decisions rationale, path-to-promotion/acceptance guidance, and a mandatory badge status note including the universal Powered by Gaia badge. Use after curation completes, before or immediately after merge for accepted intakes, or immediately upon rejection.
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。
Publish finished creatives as live Meta (Facebook/Instagram) ads via the Meta Marketing API, plus research and ad-copy support. Uploads an image or video, builds a multi-variant creative (5 bodies / 5 titles / 3 descriptions in an asset feed), and creates a PAUSED ad in an existing ad set. Also pulls top-performing ads (ranked by ROAS) and competitor ads from the Ad Library to inform copy. Use when the user asks to deploy / publish / launch a creative as a Meta or Facebook ad, build a Meta ad, push a video or image into an ad set, pull their top ads, or research competitor ads. Not for generating creative (use the image/video skills) and not for writing ad-table rows.
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。
Entry point for documentation skills covering Upstash Search quick starts, core concepts, and TypeScript SDK usage. Use when a user asks how to get started, how indexing works, or how to use the TS client.
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.
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 and revise rigorous research narratives, literature reviews, manuscript sections, citations, and figure discussions. Use for technical introductions, methods, results, discussions, review articles, abstracts, or related-work sections.
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。
Create publication-quality, editable scientific and engineering schematics with explicit physical meaning, exact labels, visual hierarchy, and provenance. Use for experimental facilities, thermal-fluid mechanisms, workflows, graphical abstracts, system architectures, or research diagrams.
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。
Provide constructive, evidence-based research mentoring feedback on student manuscripts, proposals, analyses, code, figures, and presentations. Use for advisor-style review that teaches the next improvement without impersonating an advisor or making unsupported scientific judgments.
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 clean, graphics-first technical presentations and posters with logical slide progression, visual hierarchy, purposeful motion, and complementary speaker notes. Use for research talks, conference slides, seminars, defenses, posters, or figure-focused presentations.
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 and analyze engineering experiments or simulations using baseline cases, hypothesis-driven DOE, traceable data processing, defensible plots, uncertainty, and validation. Use for CFD, laboratory data, ML workflows, parameter studies, or research code.
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。
Audit an existing mathematical, logical, algorithmic, or technical proof from its stated conclusion backward as a bounded AND/OR graph of exact obligations. Use to reconstruct conclusion dependencies, determine whether a proof-supplied route establishes the conclusion, or expose hidden assumptions, unmet side conditions, cycles, overly strong steps, or silent route switches. For a source-mapped Lamport rendering use convert-lamport, and for forward hierarchy, construct, and scope conformance use forward-lamport before this skill. This does not decide full theorem-level entailment by searching for a different proof; do not turn the audit into a linear reversed proof, exhaustive proof search, or replacement proof.
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。
Connect to and query WRDS (Wharton Research Data Services) from any research project. Use this skill whenever the user needs to download, query, or explore data from WRDS — including Compustat, CRSP, FactSet, I/B/E/S, or any other WRDS-hosted database. Also trigger when the user mentions WRDS tables, WRDS libraries, or wants to look up variable definitions or coverage in WRDS datasets. Do NOT trigger for general SQL or database questions unrelated to WRDS.
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。
Monitor brand visibility in AI search and traditional search. Use when user says "brand radar", "brand monitoring", "AI search visibility", "brand mentions", "share of voice", "who mentions my brand in AI", "brand in ChatGPT", "brand in Perplexity", "how visible is my brand", "brand awareness tracking", "AI brand presence", "is my brand cited in AI responses".
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。
DigiKey part search, stock and pricing checks, and datasheet sync. Load the canonical Circuit Weaver skill from `skills/digikey/SKILL.md`.
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。
Search LCSC Electronics for electronic components — find parts by LCSC number (Cxxxxx) or MPN, check stock/pricing, download datasheets, analyze specifications. Sister company to JLCPCB, same parts library. Sync and maintain a local datasheets directory for a KiCad project. No API key needed — uses the free jlcsearch community API. Use this skill when the user mentions LCSC, JLCPCB parts library, JLCPCB assembly parts, production sourcing, Cxxxxx part numbers, needs to find LCSC equivalents for parts, is preparing a BOM for JLCPCB assembly, or wants to download datasheets and LCSC is available. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
Search Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
Mouser part search, price comparison, and datasheet sync. Load the canonical Circuit Weaver skill from `skills/mouser/SKILL.md`.
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。