2,074 件 ・ 関連度順
概要と使いどころ
Structures pre-trade compliance with restricted list screening, position limits, and regulatory constraint verification. Use when running pre-trade compliance, screening restricted securities, or verifying trading limits.
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。
Research-backed template refresh workflow for updating existing templates with placeholder verification and rendering 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。
Research-backed JSON Schema refresh workflow for updating existing schemas with validation checkpoints and cross-reference verification.
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。
Autonomous iteration loop with dual-mode support. Standalone mode uses Stop hooks (RALPH_ACTIVE=1). Multi-agent mode uses router-managed iteration. Never traps the host/router session.
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。
Verifies implementation plan quality across 8 dimensions (requirement-coverage, task-completeness, dependency-validity, scope-sanity, artifact-wiring, risk-assessment, testability, estimation-quality) and returns pass/fail with per-dimension scores.
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。
Sequential thinking and structured problem solving. Break down complex problems into steps with revision and branching capabilities. Use for multi-step analysis, planning, and hypothesis verification.
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。
Smart contract and secure API contract security analysis — invariant checking, access control, reentrancy, and integer overflow patterns. Implements Checks-Effects-Interactions pattern, formal invariant verification, and OpenSCV vulnerability taxonomy for Solidity/EVM and Rust/Solana contracts.
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。
Orchestrates SDD project initialization — version detection, environment verification, scaffolding, and git setup.
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 international trip planning: turns "I want to go to X for N days" into a verified, bookable plan — route skeleton across cities, flight price scans (international + domestic legs), train-vs-fly decisions, hour-by-hour daily timelines with opening hours, dwell times, holiday collisions and tappable turn-by-turn map links (小时级行程+地图导航+离线KML), hotel shortlists by neighborhood, budget rollup, and a booking checklist with deep links. Use this whenever the user asks to plan a trip, vacation, itinerary or honeymoon, compare flight dates/prices, pick between cities or routes, schedule a travel day hour by hour, fill a spare block of time ("I'm near X with 2 free hours"), turn a finished plan into a designed page (eight themed renders: illustrated / clay / noir / glass / journal / zine / splash / portal — 插画/黏土/夜航/玻璃/手账/Zine/闪屏/穿越版), or asks 旅行规划/行程安排/机票比价/去某国玩N天怎么安排/现在有空档干嘛/把行程做成好看的网页 — even if they only mention one piece (just flights, just hotels, or just navigation), the playbook and verification rules here still apply.
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。
Phase 4 of 5 — implements tasks from TASKS-<N>-<slug>.md (with ARCH-<N>-<slug>.md as architecture-only context) using mode-appropriate verification (tdd, test-after, ui, checklist); pass 'auto' to run without stepping. Use only when the user asks to run Phase 4 or implement tasks from an ARCH doc — never trigger automatically from a coding request.
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。
Phase 3 of 5 — slices the ARCH doc into verification-ready task specs (tdd/test-after/ui/checklist), emitted as a separate TASKS-<N>-<slug>.md file alongside ARCH for the implement skill. Use only when the user asks to run Phase 3 or generate tasks from an ARCH doc — never trigger automatically.
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。
Create isolated git worktrees with smart directory selection and safety verification
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 before EZ_math_model declares quality_audit, packaging, or final delivery complete, especially when pass/fail claims must be backed by files, commands, counts, or concrete evidence.
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。
Guide the team through writing a change-impact record for IEC 62304 / FDA / ISO 26262 ASIL C+ projects. Surfaces the affected REQ/DES/TEST/CODE artefacts and captures human-attested verification approach.
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 research with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".
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。
Trains the HUMAN user's critical thinking through four modes: drill (argument-analysis items with a single defensible answer, judge stance), scene (Socratic exploration of synthetic scenes or user-supplied material, no verdicts on interpretations; includes a configure track — design the information request and verification plan for a decision before any analysis), expedition (guided audit of impossible-tier problems from verified packs), and detective (a runtime-generated multi-layer case worked as an escape room, guide-and-judge stance). Use when the user wants to practice critical thinking, analyze arguments, hunt assumptions, examine bias, train reasoning, or decide what information a decision needs first. Triggers: critical thinking practice, train my thinking, drill, scene, byom, configure, information plan, what would I need to know, spot manipulation tactics, scam literacy, 批判思考練習, 話術辨識, detective, 查案, 破案, 偵探.
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 a repository's type system and generate type-safe DAG execution pipelines with GraphSentry-style certificate verification. This skill should be used when building LLM-driven workflows that need deterministic type safety, when composing typed operations into validated execution graphs, or when adding contract-checked pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).
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 Brain /brain-review: after verification or before public/shipping decisions.
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 verification depends on agent runtime phases, queued input, tool-call lifecycle, save points, retry, abort, compaction, or branch 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。
Evaluates whether work-in-design is ready to hand off from a chat design conversation to autonomous execution (Claude Code, n8n, agent runtime). Runs a 7-condition gate: spec stability, verification surface, invariants, pump-primer, work decomposition, rollback cost, token budget headroom. Three invocation modes — deliberate (caller provides work_context, returns JSON verdict), proactive sensing (Claude detects handoff signals in design conversation and offers the check), conversational walkthrough (Claude walks the 7 conditions as discussion topics). Returns structured JSON in all modes. Use when designing a Claude Code deployment, scoping an autonomous run, or deciding next move. Trigger on: "ready to hand off," "ready for execution," "is this CC-ready," "handoff check," "walk me through readiness," "are we ready to ship this," "should I just hand this off," or proactive detection. Do NOT use for evaluating completed work, runtime selection, or prompt quality. Profile-agnostic.
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 a pull request end-to-end using GitHub CLI. Covers diff analysis, commit history review, CI/CD check verification, severity-leveled feedback (blocking/suggestion/nit/praise), and gh pr review submission. Use when a pull request is assigned for review, performing a self-review before requesting others' input, conducting a second review after feedback is addressed, or auditing a merged PR for post-merge quality assessment.
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。
Export and optimize 3D models for FDM/SLA printing including STL/3MF export, mesh integrity verification, wall thickness checking, support generation, and slicing. Use when exporting from CAD or modeling software for 3D printing, verifying STL/3MF files are printable before slicing, troubleshooting models that fail to slice correctly, optimizing part orientation for strength or surface finish, or converting between model formats while preserving printability.
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。
Contribute to OpenClaw ecosystem projects (OpenClaw, NemoClaw, NanoClaw) through a structured 9-step workflow: target verification, codebase exploration, parallel audit, finding cross-reference, and pull request creation. Emphasizes false positive prevention and project convention adherence.
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 a data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.
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。