6,442 件 ・ 関連度順
概要と使いどころ
Use when filing an approved task spec as a GitHub issue with a local archive and optional worktree implementer. Don't use for spec drafting without human interrogation and redaction gates.
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 deciding what an interface should do before UI is built or audited: consequences, action scope, reachable states, naming, and accessibility. Not for visual implementation: use prototype.
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 any bounded workflow starts or reaches an action, path, proposal, or merge boundary. Refuses rather than default-allow on an unreadable constraint set.
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 asks to simplify, clean, or refine code. Not for new abstractions or whole-codebase refactors.
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。
Assess and route one bounded Proto UI dependency drift, advisory, or update question. Use to trace manifest and lockfile identity, consumer impact, compatibility evidence, provenance, update risk, and the exact next update or no-action transition. This leaf remains read-only.
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 one bounded Proto UI collaboration-governance slice and route policy-determined drift toward reversible correction. Use across Issues, pull requests, Discussions, labels, milestones, Project, rules, permissions, or Actions. This evidence leaf is read-only; authorized corrections continue in their registered leaves.
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。
Apply one independently reviewable numeric Proto UI package-budget increase for an already accepted capability, using canonical cost evidence and existing development authorization. Use for standalone ceiling transactions, not feature implementation, measurement-policy changes, spending limits, publication or release.
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 one bounded Proto UI Actions or CI failure from an exact workflow run and revision, then route the exact repair, validation, or recheck transition. Use to locate the owning failure and distinguish infrastructure from change failures. This leaf remains read-only.
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。
Fix silent failures when parsing Grafema semantic IDs that are in URI format instead of legacy arrow format. Use when: (1) code splits semantic IDs by "->" but gets the whole string back because IDs are grafema:// URIs, (2) file path extraction from semantic IDs returns empty or wrong values, (3) derived edges (DEPENDS_ON, etc.) produce 0 results despite source edges existing, (4) any code that processes semantic IDs after the analysis pipeline's to_uri_format() has run. The grafema:// URI format uses # fragments with percent-encoded characters instead of -> separators.
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 React + Three.js (or any browser canvas) frame stutter by capturing a CDP CPU profile via Playwright instead of guessing from `[perf]` console logs. Use when: (1) frame time is bad but `[perf]` instrumentation doesn't pinpoint the offender, (2) you've spent more than ~30 minutes "fixing" suspects without measuring, (3) hot paths involve animation systems, allocation bursts, or invisible scene-graph traversal, (4) you need self-time per function with line numbers, not aggregate "render slow". The `console.warn` pattern is good for monitoring; CDP is needed for diagnosis. Covers script template, sourcemap setup so minified function names are decoded, and interactive variant where the user drives the interaction and signals stop via `touch /tmp/<flag>`.
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。
Recover from stale RFDB nodes that survive `commit_batch` cleanup despite having their `file` field listed in `changed_files`. Use when: (1) re-running an enricher/orchestrator step but old data with the same file field stays in the graph, (2) `commit_batch(changed_files=[X], ...)` reports success but a query later still returns nodes with `file = X`, (3) you re-pointed structural nodes (e.g., DIRECTORY/FILE) from a synthetic file path to real file paths and the old synthetic-path nodes won't go away, (4) graph-stream / find_by_type returns a mix of "stale" and "new" nodes for the same logical entity. Root cause: `handle_commit_batch` calls `engine.find_by_attr({file: X})` to enumerate nodes-to-delete, but that query path returns only a PARTIAL set after compaction (L1 segments and the file→nodes index can desync). Workaround: enumerate stale nodes via the TS rfdb client `queryNodes({file: X})` (different code path that finds all of them) and call `deleteNode(id)` per node, then re-commit the intended state. Related: rfdb-manifest-l1-carryforward (same L1 family).
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 build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.
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 actions in Linear (read, create, update, search issues, projects, comments, teams, cycles, labels, etc.) by writing and running small Node scripts against the official @linear/sdk TypeScript SDK with a personal API key. Use this when the user wants to do Linear work from the terminal without the Linear MCP server, or asks to list/open/create/update/close Linear issues, leave comments, or query teams, projects, users, or workflow states.
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。
End-to-end system for creating supervised fine-tuning datasets from books and training style-transfer models. Covers text extraction, intelligent segmentation, synthetic instruction generation, Tinker-compatible output, LoRA training, and validation.
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。
Automate browser interactions, test web pages and work with Playwright 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。
Apply product-grounded visual quality constraints during user-visible UI changes. Use for layout, styling, content hierarchy, theming, responsive behavior, or interaction affordances. Stay inactive for logic-only changes that preserve the rendered interface.
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。
Review or polish a product UI for accessibility, brand fidelity, hierarchy, rhythm, responsive behavior, themes, interaction states, and generic AI-template patterns. Use for visual audits, accessibility checks, UX polish, UI critique, or pre-ship design review. Do not use for generic code review, backend review, or API design.
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 actions in Linear (read, create, update, search issues, projects, comments, teams, cycles, labels, etc.) by writing and running small Node scripts against the official @linear/sdk TypeScript SDK with a personal API key. Use this when the user wants to do Linear work from the terminal without the Linear MCP server, or asks to list/open/create/update/close Linear issues, leave comments, or query teams, projects, users, or workflow states.
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。
Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish".
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。
Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence. Use when asked to "open in browser", "test the site", "take a screenshot", or "dogfood this".
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 PDF Report Generator — scans current directory for RECRUIT-*.md files, extracts scores and data, generates polished client-ready PDF with cover, score gauge, dashboard, and prioritized action plan
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。
Hiring Pipeline Status Report — active roles, candidate counts by stage, time-in-stage analysis, bottleneck identification, recommended next actions
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。
Launches 5 parallel AI agents to produce a comprehensive recruiting and hiring readiness analysis with composite Hiring Readiness Score (0-100), grade, and prioritized action plan
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 an actionable markdown implementation plan, without executing it.
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。