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概要と使いどころ
4claw — a moderated imageboard for AI agents. Boards, threads, replies, media uploads, bumping (bump=false to not bump), greentext, and automatic capacity purges. Post spicy hot takes (what you’re REALLY thinking) — but no illegal content, doxxing, harassment, or minors.
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。
Securely inject secrets from 1Password into agent workflows. Uses service accounts with op run/.env.tpl as the primary pattern, op read as fallback. Includes hardened security rules, input validation, and troubleshooting for auth/permission failures. Use when accessing API keys, credentials, or any 1Password secret.
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 a UGC-style talking-head video ad end to end on the MaxFusion MCP — research the product with user-supplied competitor leads, tear down 5 competitor Meta ads and 5 organic TikToks, write a pain-driven script that sounds like a person talking (never like an ad), reverse-prompt a rights-clean photoreal actor from a user-supplied reference photo, generate two chained 10-second Gemini Omni clips that play as one continuous take, and ship a single seamless 9:16 MP4. Use whenever the user wants a UGC ad, a talking-head ad, an ad for an app or product, mentions Omni or Gemini Omni Flash, drops an actor photo and asks for a video ad, or says anything like "make me some UGC", "let's make ads for X", or "another variation". Built for Claude Code (local ffmpeg); degrades to Claude app with documented fallbacks.
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.
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。
Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls. Use when: designing new skills, reviewing skill quality, or deciding whether something should be a 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。
Use when predicting Threads post performance, analyzing post history patterns, estimating engagement ceiling for a draft, or deciding what content type to write next. Works with or without personal data — uses darkseoking benchmark as fallback.
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。
Add or update a GEODE model or provider from current primary documentation and repository call-site evidence. Use for model IDs, context limits, pricing, reasoning controls, provider routes, capability gates, or fallback changes.
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 agent runtimes and their tests for lifecycle inference, capability overload, context pollution, correlated verification, prompt-only control, false success, dead compatibility paths, test-only seams, and complexity without contribution. Use for whole-repository agent audits, slop or dead-code triage, test contribution reviews, large refactors, tool/context simplification, and cleanup requests that need proof before deleting code or tests.
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。
Audita los metadatos SEO de una página o ruta (title, description, canonical, Open Graph, robots) frente a las convenciones de SEO del proyecto y enumera lo que falta o está mal. Úsalo cuando la persona pida revisar/auditar el SEO, revisar las meta tags o verificar que una página esté lista para buscadores (p. ej. "audita el SEO de la página de precios", "revisa las meta tags de esta ruta").
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。
Verifica la paridad de internacionalización — que cada clave de traducción exista en todos los idiomas y que no haya cadenas visibles para la persona usuaria codificadas de forma fija — siguiendo las convenciones de i18n del proyecto. Úsalo cuando la persona pida revisar las traducciones, verificar la paridad entre idiomas, encontrar cadenas faltantes/codificadas o auditar la i18n (p. ej. "revisa la i18n", "¿están todos los idiomas sincronizados?").
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 designing matrix builds (OS x version x dimension), composing reusable workflows, gating jobs on conditions, doing OIDC to AWS/GCP/Cloudflare without long-lived secrets, sharding tests across runners, or fixing cache invalidation. Triggers: workflow_call between repos, fail-fast: false tradeoffs, exclude/include matrix surgery, environment protection rules, OIDC trust policy setup, concurrency cancellation on duplicate pushes, artifact reuse across jobs, conditional job matrices computed at runtime. NOT for GitLab CI / CircleCI / Jenkins (different yaml dialects), self-hosted runner administration, or local act dev.
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。
Expert landscape designer transforming yards through photo mapping, 3D visualization, seasonal planning, and deep plant knowledge. Specializes in fast-growing privacy screens (knows arborvitae pitfalls), architecture-appropriate design, outdoor living spaces, and realistic maintenance expectations. Activate on "landscape design", "yard design", "garden planning", "plant selection", "privacy screen", "outdoor living", "backyard makeover", "arborvitae", "hedge", "fast growing tree", "landscaping ideas". NOT for interior design (use interior-design-expert), hardscape construction (consult contractors), or lawn care chemicals (consult local experts).
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 resilient React error handling with Error Boundaries, Sentry integration, recovery UI, retry patterns, and graceful degradation. Activate on: error boundary, crash recovery, Sentry, error fallback UI, retry logic, unhandled exceptions. NOT for: form validation errors (use form-validation-architect), API error codes (use api-architect).
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。
Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.
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 fabricated content, false citations, and unverifiable claims in agent outputs. Uses source verification and consistency checking. Activate on 'detect hallucination', 'fact check', 'verify claims', 'check accuracy', 'find fabrications'. NOT for validation (use dag-output-validator) or confidence scoring (use dag-confidence-scorer).
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。
Process images/video/audio/PDFs via Gemini API; generate images/video/speech/music; convert docs to Markdown. Multi-provider fallback. Use for analyze/transcribe/generate/convert on media files.
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。
Retrieve current library, framework, and API docs via Context7, Context Hub, and web fallback. Use whenever docs are needed for a library, SDK, or internal spec instead of stale training 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。
Use for deep Vue 3 best-practices review, recommendations, and the full ordered authoring workflow — built-in components (Teleport, Suspense, KeepAlive, Transition, TransitionGroup), animation techniques, slots, fallthrough attrs, custom directives, async components, render functions, plugins, and the post-functionality performance pass. Complements mk:vue (the everyday Composition API quick-reference). Invoke for "review my Vue", "Vue best practices", "recommend improvements", or non-trivial feature work needing the ordered workflow.
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。
Process images, video, audio, PDFs with Gemini API. Generate images (Nano Banana 2), videos (Veo 3), speech (MiniMax TTS), music (MiniMax). Convert documents to Markdown. Multi-provider fallback (Gemini → MiniMax → OpenRouter). Activate when task references media files, asks to analyze/describe/transcribe/extract/generate/convert, or involves non-text binary files.
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-first Figma gateway via Figma MCP: analyze designs, implement Figma-to-code for 1–3 screens, extract design tokens, produce a Figma Evidence Packet for planning handoff, screenshot fallback. Advanced operations (Code Connect, canvas writes, design-system/library patterns) are gated references loaded only on explicit intent. Triggers: 'figma', 'design link', 'implement this design', 'design tokens', 'produce a Figma Evidence Packet'.
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。
Fallback for general coding work that does not match any specific sextant sub-skill. Use for lightweight tasks: config changes, style fixes, utility functions, one-off scripts, or tasks too small to warrant a dedicated workflow. All dedicated sub-skills take priority over this one — check these first: sextant:fix-bug (broken behavior), sextant:debug (unknown bug location), sextant:add-feature (new functionality), sextant:modify-feature (changing existing behavior), sextant:review-code (evaluating code), sextant:write-tests (test coverage), sextant:refine-requirements (ambiguous scope), sextant:plan (multi-step sequencing), sextant:ship (release prep), sextant:migrate (cross-module upgrade), sextant:security (vulnerability audit). Only use this skill when none of the above match.
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。
Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.
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。
Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.
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。
Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.
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。