1,022 件 ・ 関連度順
概要と使いどころ
Create custom modules for [Harbor Boost](https://github.com/av/harbor/tree/main/boost), an optimizing LLM proxy. Use when building Python modules that intercept/transform LLM chat completions—reasoning chains, prompt injection, structured outputs, artifacts, or custom workflows. Triggers on requests to create Boost modules, extend LLM behavior via proxy, or implement chat completion middleware.
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。
Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.
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 refactoring expert for improving code quality, reducing technical debt, and safe transformations
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 in historical alchemy, Hermetic philosophy, and symbolic transformation from medieval to modern esoteric traditions
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。
Fourier analysis specialist covering series, transforms, signal processing, and harmonic analysis
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。
Applied math expert for engineering applications including Fourier analysis, transforms, and practical problem solving
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 in vector spaces, matrices, linear transformations, eigenvalues, and applications to data science and machine learning
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 Skmtc CLI to scaffold projects, install or clone generators from JSR, configure schema sources and enrichments, and produce code artifacts from an OpenAPI v3 or GraphQL SDL schema. Teaches the workspace mental model (`<root>/.skmtc/<project>/`, client.json, bundle, manifest) and the agent contract (strict text / strict JSON modes, exit codes, recipe errors, `agent-context` + `doctor`); the command surface itself is discovered from the binary — `skmtc --help`, `skmtc <cmd> -h` — rather than carried in this skill. Use this skill when the user asks to "run skmtc", "generate code from an OpenAPI schema", "install a skmtc generator", "scaffold a skmtc project", "watch a skmtc project", "configure enrichments", "publish a stack", "deploy to skmtc-hub" (the command is `publish`; there is no `deploy`), "skmtc in CI", or invokes any CLI subcommand. For *authoring* a generator package (Projections, Snippets, transform functions), defer to `skmtc-generator`. When something is broken (no output, wrong output, error messages, a failed bundle build), verify before proposing a fix: read the manifest and the parse issues, and reproduce the failure first.
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。
Register shared claims transformation and hierarchical role policies in the API without breaking existing scope enforcement.
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。
Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
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。
Universal project bootstrapper: CREATE new or TRANSFORM existing project to production-ready structure
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 .pi/skills from procedural doc sections with proper structure and transformation
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。
Scientific research engine for hypothesis testing, literature gap analysis, experimental validation, and data-driven discovery. Enforces adversarial review (Reviewer 2), 32 quality gates, tree search over hypotheses, confounder harness for quantitative claims, and serendipity detection. TRIGGER when: user asks to analyze scientific data, test hypotheses, validate findings, search for research gaps, design experiments, or investigate results. DO NOT TRIGGER when: pure code review, documentation writing, devops tasks, general conversation, or non-scientific data transformation.
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 10 advanced AI agent node types for any DSL/runtime system — plan compiler, code interpreter, critique loops, intelligent routing, multi-agent ensemble, persistent memory, external API tools, iterative loops, data transforms, and parallel execution. Use this skill whenever the user wants to add agent capabilities to a workflow engine, build an AI orchestration framework, implement Karpathy-style AI upgrades, add new node types to a DSL runtime, or create autonomous agent pipelines. Also trigger when the user mentions AetherLang, flow engines, node types, agent frameworks, or wants to upgrade their AI system with capabilities like self-programming, reflection, routing, ensemble, memory, or tool use.
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 a (blog post/novel/speech etc)
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。
Transform learning content (like YouTube transcripts, articles, tutorials) into actionable implementation plans using the Ship-Learn-Next framework. Use when user wants to turn advice, lessons, or educational content into concrete action steps, reps, or a learning quest.
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。
Automatically organize invoices and receipts for tax preparation by extracting key information, renaming files consistently, and sorting into logical folders. Transform chaotic bookkeeping into tax-ready records.
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。
Transform technical git commits into polished, user-friendly changelogs and release notes. Automatically categorizes changes, translates developer language into customer-friendly copy, and generates professional changelog 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。
Transforms police body camera transcripts into structured 10-section legal summaries with timestamp-cited verbatim statements, constitutional issue spotting, evidence inventory, and probable cause articulation. Maintains strict neutrality for all parties. Use when analyzing BWC footage for discovery, pre-trial prep, or trial. Trigger: body camera, BWC, body worn camera, officer footage, use of force review, incident summary.
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 transforming existing code into agent-consumable surfaces — CLI (npm-publishable), MCP server (stdio/SSE/Streamable HTTP), and a companion skill. Triggers on 'agentize', 'henshin', 'expose as MCP', 'wrap as CLI', 'publish to npm', 'make LLM-accessible', 'turn into agent tool', 'expose feature as tool'. Runs when the user has existing code and wants to ship it to agents. NOT for building new code from scratch (see mk:bootstrap); NOT for reviewing or verifying existing code (see mk: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。
Process, analyze, and visualize geospatial data at scale. Handles drone imagery, GPS tracks, GeoJSON optimization, coordinate transformations, and tile generation. Use for mapping apps, drone data processing, location-based services. Activate on "geospatial", "GIS", "PostGIS", "GeoJSON", "map tiles", "coordinate systems". NOT for simple address validation, basic distance calculations, or static map embeds.
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。
Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview preparation.
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。
AI-powered career biographer that conducts empathetic interviews, extracts structured career narratives, and transforms professional stories into portfolios, CVs, and personal brand assets. This skill should be used when users want to document their career journey, create professional portfolios, generate CVs, or craft compelling career narratives.
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。