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Use when the user asks to create a new branch or start work on one. Not for remote, credential, publish, deploy, or irreversible changes.

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 a workflow, plan, diff, or completed work cycle must be checked for practices that punish the project later. Not for source, remote, credential, publish, deploy, or irreversible changes.

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 an artifact or skill has just changed and is about to be called done, committed, or handed off. Not for remote, credential, publish, deploy, or irreversible changes.

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 a user needs coverage-guided fuzzing for Python code or a Python native extension using Atheris. Not for remote, credential, publish, deploy, or irreversible changes.

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 asked to implement under non-negotiable constraints: performance budgets, platform limits, legal or API rules. Not for remote, credential, publish, deploy, or irreversible changes.

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 make the skills framework work in a new harness, IDE, or CLI. Not for remote, credential, publish, deploy, or irreversible changes.

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 writing or verifying framework-specific code, boilerplate, or a documented, correct implementation. Not for remote, credential, publish, deploy, or irreversible changes.

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 asked to optimize code, make a path faster, make this as fast as possible, reduce allocations, repair a regression, profile a target, grill every inefficiency, or run a subsystem or repo-wide performance campaign against a measured floor; when a performance requirement, slowness report, Core Web Vitals miss, or profiling evidence identifies a bottleneck; or for an "extremely optimize" performance campaign, optimizing suspected hot paths without waiting for benchmarks, or estimating hot and complexity-neutral cold paths while refusing complexity theater. Not for remote, credential, publish, deploy, or irreversible changes.

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 says deslop, debloat, tidy, simplify, clean a diff, cleanup codebase, or deslop branch diff, or remove dead code or config. Not for remote, credential, publish, deploy, or irreversible changes.

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 onboarding to a repository, capturing costly conventions, constraints, or rationale, or improving AGENTS.md. Not for remote, credential, publish, deploy, or irreversible changes.

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 a user wants to define patterns the agent should not do. Don't use for remote, credential, publish, deploy, or irreversible changes.

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 asked to run AST-based structural search, lint, or rewrite of code when regex is too fragile. Not for remote, credential, publish, deploy, or irreversible changes.

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 non-trivial code needs a design, codebase design or architecture needs improving, or one module needs targeted interface narrowing, seams, or testability. Not for diagrams, deploy, or irreversible changes.

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 project and generate Docker configuration: Dockerfile (multi-stage dev/prod), compose.yml, compose.override.yml (dev), compose.production.yml (hardened), and .dockerignore. Includes production security audit. Use when user says "dockerize", "add docker", "docker compose", "containerize", or "setup docker".

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。

Audit one bounded Proto UI deployment or publication evidence slice against an exact revision and delivery surface. Use to verify revision identity, environment result, artifacts, and observable health. Do not deploy, promote, roll back, publish, release, or change environment protection.

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 Odylith Discipline pressure behavior, zero-credit hard laws, host/lane parity, or benchmark-proved learning-spine contracts need 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。

Fix docker exec hanging when starting background processes (servers, daemons) inside containers. Use when: (1) docker exec never returns despite using & or nohup, (2) background server started in container causes docker exec to hang indefinitely, (3) env_startup_command in SWE-bench or similar frameworks times out, (4) setsid/disown needed for proper process detachment in Docker. Root cause: docker exec tracks ALL processes in the exec session, not just the top-level PID.

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 RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers 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 Node.js CLI tools crashing inside Docker containers when host-installed node_modules require a newer Node version than the container provides. Use when: (1) "SyntaxError: Invalid regular expression flags" with /v flag in string-width or similar packages, (2) node_modules installed on host with Node 20+ but container has Node 18, (3) `npm install` with file: protocol creates symlinks that break inside Docker, (4) pnpm workspace packages become broken symlinks in containers. Covers version detection, Node binary mounting, and npm install strategies for cross-version compatibility.

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。

Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, SDK usage, and vector search. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.

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。

Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.

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。

Troubleshoot local AWS Bedrock authentication and region configuration for the Cline CLI as Dr. Bedrock. Use when users report Bedrock CLI errors, AWS profile/default-chain issues, credential_process/SSO/IAM credential failures, missing region, AccessDenied, model access, or provider config problems.

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。

Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.

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。