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概要と使いどころ
ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.
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。
act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.
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 Caliper to run real agent tasks with and without a skill, MCP server, or rule change so reliability and token cost are measurable.
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。
AgentQL is TinyFish's web automation and extraction toolkit that layers a natural-language query system on top of live sites. Its Python and JavaScript SDKs integrate with Playwright and let agents target data and interface elements without depending on brittle CSS selectors alone.
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。
Checks evidence about an unfamiliar autonomous agent before delegation, verifies signed Agent Guild passports, and returns a bounded hire, caution, or avoid recommendation without taking consequential action.
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。
Wire builders' isolated tdmcp tool files into the shared registries, CLI, and docs as a single writer, conflict-safe, and confirm a green typecheck + build. Use when integrating/wiring/registering new tdmcp tools, adding their CLI commands, resolving build breaks after parallel feature work, or merging several builders' files into the registry without conflicts.
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 focused tdmcp tests for one assigned coverage gap. Use for Vitest/msw unit tests, integration tests, bridge tests, CLI/config/resource tests, and regression tests that should raise coverage without weakening behavior.
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 optimize AI agent credit usage by routing tasks to the most cost-efficient execution path. Use when you want to reduce AI API costs by 30-75% without quality loss, classify task complexity before execution, route simple tasks to free or low-cost models, split complex tasks into optimized sub-tasks, or detect vague prompts before wasting credits.
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 and decompose a product topic into a text-only proposal for the repository's .pm board. Use when the user wants to pressure-test scope, size milestones, identify dependencies, or prepare exact PM board commands without writing board 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。
Use the gda CLI to build, inspect, validate, and export Godot projects without opening the editor, or to inspect and control a running game through gda-daemon. Use when an agent builds or modifies a Godot game, or the user asks for gda or Godot 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。
Active Directory reconnaissance with or without credentials: user/group/computer enumeration, ACL/delegation, ADCS, modern Windows LAPS, BloodHound, Server 2025/dMSA/Ghost SPN candidates, and trust mapping. Recon only — do not exploit Kerberoast-to-DA, DCSync, or change passwords. Operator may select /ad-attack after cards are ready.
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。
Enforces decisive execution without confirmation requests; suppresses redundant explanations and prioritizes direct action.
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 user wants Codex to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Codex without changing the generated Python harness 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。
Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".
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。
Hot-reload a Python function implementation from the latest file content without restarting the process. Use this to apply code fixes live after identifying a bug with watch/trace.
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。
Diagnose CircleCI failures for a branch, PR, and scheduled nightly builds. Use when asked to check CI, a build, or nightly; report evidence and suggested fixes without opening a PR.
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 on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure — identical mechanics, a different decision at step 5/8. Phase 0 also defines compressed intake, the path a user's explicit "just build it" choice takes on full-stack-app, pwa-app, authored, and copywriting cores: one batched round of questions in place of the shelf, writing a thinned archive at the same paths so Phase 1 (or, on copywriting, that core's own mining step), `ux-planner`, and the Re-entry pass all keep their documented source. Also use for the Re-entry pass, which mines new scope into additional intents without re-running the shelf, on any core with a module axis to add an intent to (full-stack-app, pwa-app, authored) — landing-page has none, so its own new-scope path runs through `hedgehog-landing-loop`'s Correction Protocol instead. Invoked by the `planner` agent, which decides the path; don't run standalone. landing-page runs this skill's Phase 0 on first run, then mines the same archive through `hedgehog-landing-loop`'s own planning-intake section, that core's counterpart to this skill's Phase 1. copywriting runs this skill's Phase 0 the same way (full or compressed), then mines the same archive through `hedgehog-copywriting-loop`'s own planning-intake section into a what/audience/register brief — no module axis, so its own new-scope path runs through that loop's Correction Protocol rather than the Re-entry pass below. An authored core runs this skill's Phase 0, then `hedgehog-core-design`, then this skill's Phase 1 mining against the designed layer sequence. A brownfield adoption (`hedgehog-adopt`) never runs this skill's shelf at all — the drivers BMAD elicits are already settled facts of a repo that already exists.
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。
Edits existing Stitch screens with text prompts — the iteration tool. Change colors, layout, content, or style without regenerating from scratch. Supports refinement loops via output_components suggestions.
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。
Converts a Stitch screen, a local HTML file, or a URL into modular Vite + React components — TypeScript, theme-mapped Tailwind, dark mode via CSS variables, and clean component architecture. Use this for Vite/React apps without App Router. For Next.js 15 App Router, use stitch-nextjs-components instead. Only the Stitch route needs an API key.
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 verifying that a model in the imp inference engine produces coherent output without repetition loops, token-stuck states, or state corruption across turns or streams. Triggers on "degenerates", "check degeneration", "repetition loop", "own own own", "stuck token", "empty content", "multi-turn regression", "does it still work", "NIAH", and after enabling CUDA graphs / changing forward pass / MoE routing / KV cache or KV dtype / GDN state or scan / sparse attention / PDL / speculation (MTP, n-gram) / ragged prefill / batched-decode kernels (smallm, producer quantize) / FA2 softmax.
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。
ALIGN-video for Codex. Create or revise a video through agent-authored code, rendering, editing and fresh-context audiovisual review, without image, video or music generation models. Use for reference-led animation, procedural films, motion design, explainers, construction replays, and continuing an existing coded-video project. Carries the work from reference study and animatic through a finished, reproducible film; supports explicitly requested self-review when appropriate.
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。
ALIGN-video for Claude Code with independent Codex adversarial review. Create or revise a video through agent-authored code, rendering, editing and fresh-context audiovisual review, without image, video or music generation models. Use for reference-led animation, procedural films, motion design, explainers, construction replays, and continuing an existing coded-video project. Carries the work from reference study and animatic through a finished, reproducible film; supports explicitly requested self-review when appropriate.
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 a site's existing WebMCP tools to AgentLane without rebuilding them. Use when a codebase already registers document.modelContext tools — natively or through any SDK — and the developer wants them visible in AgentLane, migrated onto @nekuda/webmcp-sdk with durable stable keys and verified to behave exactly as before.
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 building, debugging, or documenting Telegram bot polling flows that need safe agent routing, state tracking, and final-only replies without webhooks.
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。