1万 件 ・ 関連度順
概要と使いどころ
Review all uncommitted changes before pushing. Checks for dead code, stale comments, AGENTS.md rule violations, unused imports, and inconsistencies introduced during the current session. Invoke with $review-before-commit.
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 SQLite "database disk image is malformed" errors caused by corrupted FTS5 indexes. Use when: (1) UPDATE/INSERT fails with "stepping, database disk image is malformed" but PRAGMA integrity_check returns "ok", (2) Only specific records fail to update while others succeed, (3) Records contain dirty text with tabs, newlines, or unusual characters that were inserted into FTS5-indexed columns. The misleading error message suggests disk corruption, but the actual issue is FTS5 index corruption from malformed text content.
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 NIP-98 HTTP authentication 401 errors caused by URL mismatch between the `u` tag and what the server expects. Use when: (1) NIP-98 auth returns 401 with "URL mismatch" error, (2) Token creation succeeds but server rejects authentication, (3) Server logs show expected vs actual URL difference. CRITICAL: Server implementations vary - some strip query params, some don't. Check the actual error message to determine which behavior applies.
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 database cache when external APIs aren't reliably idempotent. Use when: (1) External API claims idempotency but returns different values for same input, (2) Re-running a script creates duplicate resources, (3) Need stable identifiers across runs but external service generates new ones. Pattern: check database cache first, only call external API for genuinely new items, cache the result.
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 all uncommitted changes before pushing. Checks for dead code, stale comments, CLAUDE.md rule violations, unused imports, and inconsistencies introduced during the current session. Invoke with /review-before-commit.
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。
Optimize Nostr relay queries using NDK batch fetching. Use when: (1) Checking existence of many events one-by-one is slow, (2) Loop with individual fetchEvents calls causing N+1 query problem, (3) Need to verify multiple addressable events (Kind 30000+) exist. NDK's fetchEvents accepts arrays for tag filters (#d, #p, #e, authors), enabling batch queries that reduce hundreds of round-trips to a single 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。
Deploy funnelcake (api + relay) to ANY environment (production, staging, poc) on GKE via ArgoCD. Use when: (1) Deploying new funnelcake commits, (2) Building Docker images for GKE (amd64), (3) Running ClickHouse migrations, (4) Troubleshooting ImagePullBackOff errors, (5) Syncing staging/poc after production deployment. Covers complete workflow with PRE-FLIGHT CHECKLIST to prevent common deployment failures.
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。
Separate a messy working tree with multiple tangled features into clean, focused PRs. Use when: (1) Working tree has uncommitted changes from multiple features mixed together, (2) Need to create a PR for just one feature from a mixed working tree, (3) "git stash pop" fails with "already exists, no checkout" for untracked files, (4) Pre-commit hooks block commits due to unrelated untracked files with errors, (5) Interface changes in one feature break consumer files from another feature in the same working tree. Covers git stash workflows, branch separation, conflict resolution, and pre-commit hook workarounds. Never stack PRs — always target main.
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 "Null check operator used on a null value" errors when an object is set to null during an async await. Use when: (1) Object reference is nullified while awaiting, (2) Code accesses object with ! after await returns, (3) Cancel/dispose operations run concurrently with async operations on same object. Solution: capture local reference before await.
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 Figma designs and translate them into Flutter code using existing divine_ui components and VineTheme. Use when implementing UI from Figma mockups or when checking if a component already exists before building new. Invoke with /figma-designer.
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 misleading HTTP response header values when debugging with curl -I or curl -sI. Use when: (1) Response headers differ between curl testing and actual browser/client behavior, (2) Cache-Control or other headers show unexpected values despite correct middleware code, (3) Server-side middleware that only applies to GET requests appears to not work when testing with curl -I. The -I flag sends HEAD requests, and middleware that checks for GET method will skip processing, returning handler-level headers instead of middleware-overridden ones.
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。
Debug Fastly Compute deployments that appear successful but return stale/wrong responses. Use when: (1) fastly compute publish succeeds but version check shows old version, (2) new endpoints return 404 after deployment, (3) cache-busted requests work but regular requests fail, (4) fastly domain list doesn't show your custom domain. Covers edge propagation timing, cached error responses, and domain management API differences.
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 this agent to a running Guaardvark (self-hosted AI studio) and check what it can do right now. Use first when the user mentions Guaardvark, asks to generate images/video/music/voice locally, run a Film Crew, train a LoRA, launch a swarm, or when a guaardvark MCP tool is missing or a call fails with "not reachable" / "plugin offline".
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 implementing enable single or multiple selections.
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 an openai-guardrails-python release plan or final release candidate against the previous remote tag, determine the compatible release type, audit runtime and packaging risk, inspect current CI, and produce an English ship-or-block report. Use for pre-release readiness checks, not ordinary PR review or 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。
AutoMCM-Pro industrial-grade math modeling agent (opencode binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
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。
AutoMCM-Pro industrial-grade math modeling agent (Codex CLI binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
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。
AutoMCM-Pro industrial-grade math modeling agent (DeepSeek Harness binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
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。
AutoMCM-Pro industrial-grade math modeling agent. Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
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 Chinese monospaced compass-style PDCA or CAPD problem-solving cards using East-West-South-North-Center layout, full-width and half-width spaces, diagonal Unicode arrows, and strict Chinese character limits. Use when Codex needs to turn a problem, incident, decision tradeoff, root-cause analysis, improvement cycle, or CAPD/PDCA workflow into a square text diagram, Hermes/Discord-ready card, or Chinese 方位九宮圖 with center ◎, north Plan, east Do, south Check, west Action, and four diagonal transition arrows.
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 generate TLA+ specifications from source code (C/C++, Python) for formal verification of distributed systems. Use when users need to: (1) Generate TLA+ specs from program implementations, (2) Model distributed systems, consensus protocols, or concurrent algorithms, (3) Extract state variables, actions, and invariants from code, (4) Create formal specifications for model checking with TLC, (5) Verify safety and liveness properties of distributed systems. Particularly effective for message-passing systems, replication protocols, consensus algorithms, and distributed transactions.
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 vulnerable code to identify underlying root causes such as violated assumptions, incorrect invariants, missing validation checks, or unsafe component interactions. Use when investigating security vulnerabilities, CVEs, exploit code, or security audit findings. Infers why the vulnerability exists beyond surface symptoms, identifies systemic issues, and explains the chain of failures that enable exploitation.
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。
Scan repositories for newly disclosed CVEs in dependencies after a specific cutoff date. Takes a repository path, cutoff date (YYYY-MM-DD), and optional parameters for transitive dependencies. Parses dependency manifests (package.json, pom.xml, requirements.txt, go.mod, Cargo.toml) and lockfiles to extract exact versions. Queries vulnerability databases (OSV.dev, NVD, GitHub Advisory) to identify CVEs disclosed strictly after the cutoff date. Distinguishes between newly disclosed CVEs and previously known CVEs. Use when: (1) Performing security audits to find new vulnerabilities since last review, (2) Checking if new CVEs affect a historical codebase version, (3) Generating compliance reports showing vulnerability status at specific dates, (4) Tracking security posture changes over time. Supports npm, Maven, pip, Go modules, Cargo, and other major ecosystems.
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 source code statically to detect potential functional bugs including null dereferences, incorrect condition checks, unreachable code, inconsistent state updates, logic errors, resource leaks, and type mismatches. Report suspicious code locations with detailed explanations, severity levels, and confidence assessments. Use when reviewing code for bugs, performing code audits, or when the user asks to find bugs, detect issues, analyze code for problems, or perform static analysis.
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。