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概要と使いどころ
Universal dispatcher: run a named taffy workflow (.claude/taffy/<name>.yaml), a skill (/skill-name), or a sub-agent (@agent-name). Falls back to skills.sh registry when a skill is not found locally. Tracks all runs in .claude/state/maple.json so the maple TUI shows live progress.
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。
Perform STRIDE threat modeling for each component and trust boundary and produce a threat register. Use when reviewing a feature for security.
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。
Zephyr RTOS development — boards and devicetree, the build system (west, Kconfig, CMake, sysbuild), drivers and peripherals, BLE and networking, the kernel, storage, power, testing and debugging, security and OTA. Use this for ANY Zephyr RTOS or embedded-firmware task on a Zephyr project; it routes you to the right specialized skill via the zephyr-cli registry.
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。
Test and validate MaaFramework Pipeline JSON, recognition nodes, action nodes, CustomAction/CustomRecognition wiring, resource loading, and end-to-end task behavior. Use when running `run_pipeline`, checking OCR/TemplateMatch/ColorMatch ROI, validating `context.run_task()` results, auditing `action: Custom` or `recognition: Custom` registrations, or choosing the right resource-check command.
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。
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
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。
Attiya-Bar-Noy-Dolev atomic register emulation over message-passing. Load when designing quorum-based distributed storage, proving linearizability, or reasoning about fault-tolerant shared memory.
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。
Bridge layer connecting the Agentic AI Foundation (AAIF) governance structure — Linux Foundation stewardship of MCP, goose, AGENTS.md — to the plurigrid/asi skill graph. Formalizes AAIF-compatible skill registration, IPSIE identity profiles, and the cross-protocol interoperability surface. Maps the AAIF platinum member ecosystem (AWS, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, OpenAI) to specific ASI skill integration points.
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 run controlled experiments using the experiment-registry MCP server — domain-agnostic, pluggable, mechanically enforced. Use when you need evidence that a change actually improves behaviour.
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。
Configures CI/CD pipelines for automated Python package publishing to PyPI or GitLab Package Registry. Use when creating GitHub Actions or GitLab CI release workflows, setting up trusted publishing or API token-based PyPI authentication, configuring version management with git tags and hatch-vcs, writing pyproject.toml publishing metadata, testing packages against TestPyPI, or documenting the release process for a Python project.
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。
Decomposes a contextualized plan into atomic, independently executable tasks with complete embedded context, registered through the plan API. Use after SAM Stage 3 Context Integration produces the contextualized plan artifact — when the plan is ready for task generation with CLEAR ordering, CoVe checks, and dependency graphs for parallel execution.
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。
Verify that changed components are actually connected into the intended end-to-end system flow. Use when checking imports/exports, registrations, data/control flow, configuration consumption, call paths, and boundary compatibility after implementation.
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 architecture review, dependency graphs, coupling analysis, or circular dependency detection. Establishes project module namespaces and traces imports plus Claude plugin hook, skill, script, PEP 723, and MCP boundaries. Emits partitioned Mermaid graphs with cycle, coupling, and ownership signals; verifies contract and consequence before assigning severity. Registers diagrams as codebase-analysis artifacts.
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。
Grooms a GitHub milestone for parallel execution — batch-grooms ungroomed items, assesses scope gaps, analyzes cross-item dependencies via Impact Radius overlap, builds conflict groups, assigns items to execution waves, and persists the dispatch plan via dispatch_create_plan MCP tool. Calls dispatch_wave_start per wave to register state. Use when preparing a milestone for /work-milestone execution. Pass the milestone number as the first argument. Requires milestone items assigned via /group-items-to-milestone.
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 the PLAN artifact from SAM Stage 2 needs contextualization against actual codebase state — grounds the design plan in reality by performing scope analysis (NEW/MODIFY/COMPLETE classification), conflict detection between plan assumptions and codebase patterns, and resource mapping to concrete file paths and integration points. Produces an updated ARTIFACT:PLAN registered via MCP with a Contextualization section appended.
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。
DRAFT. Design and harden a standing Luma registration/unsubscribe webhook that enriches guests and writes to CRM or customer DB — with backfill and versioning. Not installed by deepline skills.
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。
DRAFT. Use when running a Luma-centered GTM event campaign: pull/export guests, enrich and score, draft invites and social, stage email+LI sequences paused for approval, and wire registration sync. Not installed by deepline skills.
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。
Opt-in recreation of the Bun + TypeScript framework used to build Vapi's landing-page voice agents from a ROUGH_DRAFT.md spec, including a scenario registry, language stacks, prompt composer, assistant builder, and idempotent bootstrap script. Use only when the user explicitly invokes vapi-bootstrap-framework or specifically asks to reproduce or experiment with the landing-page-agent architecture. Do not use for ordinary Vapi assistant builds; use create-assistant, create-tool, create-squad, and vapi-prompt-builder instead. Targets Bun + TypeScript + @vapi-ai/server-sdk.
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 modifying agentic contextual building blocks like skills (SKILL.md), slash commands, agents, hooks, plugins, marketplaces, and instruction files (CLAUDE.md, AGENTS.md, GEMINI.md, QWEN.md, Cursor, Copilot, Cline, or Kiro rules), tool configuration such as an OpenCode `opencode.json`, Muse Code hooks (`.muse/hooks.json`), a Grok Build `.grok/` project layer or a Google Antigravity customization root (`.agents/`, `.agent/`, `_agents/`, `_agent/` — hooks, MCP config, rules, registries and plugins), and committed project memory (`.agents/memory/`). Run skillsaw on the files you touched, apply autofixes, resolve remaining violations with `skillsaw explain` guidance, and re-lint until clean before considering the work complete.
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。
Analyze upstream specs (agentskills.io, Claude Code plugin/marketplace format, OpenAI Codex plugins/marketplace, OpenClaw, MCP and MCP Registry, CodeRabbit, APM) for changes, identify gaps in skillsaw's rule coverage, and create or update PRs to close those gaps. Use when performing periodic maintenance on the skillsaw linter.
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。
Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.
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。
Builds or audits a literature review, producing an evidence map, the closest prior work, source clusters, a gap verdict, and a synthesis plan for the introduction. Use when the user asks whether a contribution is novel, who has studied a question, what the literature establishes, or how to organize a review, or wants a reading list, Zotero export, or pile of papers turned into one. For systematic reviews or meta-analyses it produces the protocol scaffold and routes registration (PROSPERO or OSF) and screening to dedicated tools.
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。
Audits fielded survey-response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and produces an appendix-ready quality report. Use at soft launch before full field, after fielding before outcomes are analyzed, or when asked what a study did about bots and AI respondents.
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。
Provides a pre-submission manuscript audit covering argument, numerical consistency, references and DOIs, writing, figures, CONSORT flow, pre-registration, and the replication archive. Use before paper submission or when a draft needs an adversarial, quote-grounded review with a journal-readiness checklist. Add `--codex` to run the specification independently on Claude and Codex, GPT-6 Astra, and cross-check findings.
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。
Plans a research project as a decision map that persists across sessions, resolving one ticket per session until the design is defensible and pre-registerable. The map lives as Markdown in the repository, literature sweeps run as parallel research tickets, and the resolved map compiles into a pre-analysis plan. Use at project start, when a design has more open decisions than one conversation can hold, or when planning restarts each session. Not for executing analyses or writing the paper.
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。