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概要と使いどころ
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
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。
Dry-run Trust Magnitude for proposed named skills or suites before curation. Use when deciding whether a proposed suite deserves A/S treatment, when checking Fusion Score structural inputs, when comparing repo stars vs suite component counts, or when asked to appraise a candidate before adding it to the registry.
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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。
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。
Triage and classify pending Gaia skill intake batches in registry-for-review/. Use for gaia push intake proposals, draft skill batches, and deciding whether proposals should proceed to canonical curation. This skill is read-only and never promotes skills itself.
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。
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.
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.
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。
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.
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。
Performs fast first-pass triage of an unknown file to decide depth of analysis: file type identification, hashing, reputation lookup, packing/entropy check, and string review. Activates for requests to triage, classify, or do initial assessment of an unknown or suspicious file.
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 structure and indicators from a Windows PE file without executing it: headers, sections, imports/exports, resources, entropy, and embedded strings to infer capability and packing. Activates for requests to statically analyze a PE, EXE, or DLL, or inspect imports and headers.
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。
Detects DNS-based tunneling and data exfiltration in DNS logs: scoring high query volume to single domains, long/high-entropy subdomains, unusual record types, and encoded payload labels. Activates for requests to hunt DNS tunneling, detect DNS exfiltration, or analyze suspicious DNS query 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。
Locates candidate encryption keys in a binary by finding high-entropy fixed-size regions (16/24/32 bytes) near cryptographic constants or crypto API references, and surfacing printable key/passphrase strings. Activates for requests to extract encryption keys, find an AES key in a sample, or recover hardcoded crypto material.
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。
Analyzes malicious VBScript, WSF, and HTA scripts: parsing WSF/HTA containers, decoding VBScript.Encode (#@~^) and string obfuscation, and identifying WScript.Shell/ActiveX abuse to recover dropper behavior. Activates for requests to analyze VBScript, decode a WSF/HTA, or investigate a Windows Script Host dropper.
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。
Anthropic Claude API guidance — messages API, tool use, prompt caching, extended thinking, and production 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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
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。
Reviews AudioUnit v2/v3 plugin implementations for spec compliance, thread safety, and correctness. Use when the user asks to review an AudioUnit plugin, check an AUv3 app extension, audit property or parameter handling, or asks "is my AUComponent thread-safe?" or "why does my AU crash in Logic?". Trigger on phrases like "review my AudioUnit", "check my AUv3", "is my render block safe?", or when you see AURenderCallback, internalRenderBlock, kAudioUnitProperty_*, or AUAudioUnit in the 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。
Production-grade TypeScript reference for React & Next.js frontend development. Covers type narrowing, component Props, generic hooks, discriminated unions, as const, satisfies, Zod validation, TanStack Query, server/client boundaries, forms, state management, performance, accessibility, debugging, and code review. Use when the user works with TypeScript in React or Next.js: type errors, Props design, generics, API typing, SSR/CSR boundaries, hydration issues, form validation, state management, performance, or code review. Also use for "how should I type this?", "why does this type error happen?", or any architectural decision involving TypeScript in a frontend context.
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 Unity 6+ UI Toolkit Runtime Data Binding code using MVVM pattern with [CreateProperty], DataBinding, and PropertyPath. Use when creating UI screens, HUDs, menus, inventories, settings panels, or any data-bound UI elements with UI Toolkit. Triggers on requests like "create a health bar", "build the HUD", "make a settings screen", "bind data to UI", "create an inventory UI", "add a pause menu", "show player stats on screen", "build a shop UI", "create a dialogue box", or any task involving runtime UI layout, styling, or data display. Also use when the user mentions UXML, USS, ViewModel, or UI bindings. Only activates when ProjectConfig.yaml -> ui_system is "UIToolkit" or "Mixed". Requires Unity 6.0+.
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。
Unity 6 editor scripting and custom tools guide. Use when creating custom inspectors, EditorWindows, PropertyDrawers, Gizmos, Handles, menu items, or editor extensions. Covers SerializedObject/SerializedProperty pattern, AssetDatabase, and editor-only code with #if UNITY_EDITOR. Based on Unity 6.3 LTS documentation.
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。
OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.
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 a task needs the judgment of a chiropractor — screening a spinal or musculoskeletal complaint for red flags before manipulation, choosing a manipulation technique given a patient's risk profile, designing a care plan with a defined reassessment checkpoint, or deciding whether to continue, modify, or discharge a course of care.
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 a task needs the judgment of a climate change policy analyst — evaluating a proposed emissions rule's cost-benefit case, comparing carbon-pricing instruments (tax vs. cap-and-trade), drafting regulatory comment letters or legislative issue briefs, or assessing whether a climate proposal survives legal/political feasibility 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。
Use when a task needs the judgment of an agricultural engineer — sizing a center-pivot or drip irrigation system's peak capacity against crop water demand, computing lateral grain-bin wall pressure with Janssen's equation, sizing a waterway or tile-drainage system with Manning's equation and an NRCS design-storm return period, or building a manure/nutrient first-year availability mass balance against a crop's N 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。