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Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.

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 code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay". Optional +check flag validates findings via a fresh-context subagent.

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。

Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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 query issues in Grafema tests when nodes have numeric IDs instead of human-readable IDs, or when `type` field is undefined. Use when: (1) queryNodes returns nodes with numeric IDs like "52710336597754872375318185843222727675" instead of semantic IDs like "net:request#__network__", (2) node.type is undefined but node.nodeType has a value, (3) metadata is a JSON string instead of parsed object, (4) tests fail with "Cannot read property 'length' of undefined" after queryNodes. Covers RFDBServerBackend vs RFDBClient distinction and async generator handling.

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。

SWE-bench pipeline for A/B testing Grafema with Claude Code. Use when: (1) running SWE-bench experiments, (2) comparing baseline vs grafema conditions, (3) evaluating results, (4) debugging container issues.

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 and fix RFDB data disappearing after compaction, where rfdb-server reports a tiny node count (e.g. "15 nodes") on startup despite manifest_index.json showing hundreds of thousands of nodes and segment files existing on disk. Use when: (1) rfdb-server logs "Default database: N nodes" with N orders of magnitude smaller than recent analysis output, (2) /api/stats returns only the most recent commit's nodes, (3) the issue appears AFTER a compaction event (manifest with l1_node_segments populated and node_segments: []), (4) subsequent commits dropped L1 references. Root cause: ManifestStore::create_manifest() initializes l1_node_segments/l1_edge_segments to Vec::new() instead of cloning from current manifest, so any commit AFTER compaction silently orphans all L1 data even though segment .seg files still exist on disk. Compaction injects L1 fields explicitly after create_manifest, but regular commits do not.

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 Elixir/Erlang AST processing bugs in Grafema beam-analyzer. Use when: (1) Elixir parser returns MODULE node but 0 functions/calls — body nesting issue, (2) Erlang parser crashes with "cannot convert list to string" on OTP 26+ — location format changed from integer to keyword list, (3) pipe operator |> creates spurious CALL nodes instead of desugared function calls — clause ordering bug, (4) multi-module .ex files return only the first module — missing __block__ handler, (5) installing Erlang/Elixir on macOS with outdated Xcode/Clang.

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 metadata issues in RFDB node storage. Covers two traps: (1) metadata flattening — nested metadata fields become top-level after serialization, so node.metadata.field is undefined but node.field works. (2) reserved keys — fields named "type", "id", "name", "file", "exported" are silently stripped from metadata by _parseNode() to prevent overwriting top-level node fields.

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 needs to search or navigate code with Sourcegraph MCP tools. Provides disciplined search workflows for finding implementations, understanding systems, debugging issues, fixing bugs, and reviewing code.

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。

Guide for using the Sentry CLI to interact with Sentry from the command line. Use when the user asks about viewing issues, events, projects, organizations, making API calls, or authenticating with Sentry via CLI.

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。

Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.

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 code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay". Optional +check flag validates findings via a fresh-context subagent.

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。

Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the 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。

Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff".

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。

Build type-safe validated forms using React Hook Form v7 and Zod v4. Single schema works on client and server with full TypeScript inference via z.infer. Use when building forms, multi-step wizards, or fixing uncontrolled warnings, resolver errors, useFieldArray issues, performance problems with large forms.

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 Ascend NPU schedule, operator dispatch, operator launch, and Host Bound profiling issues in Ascend profiling data. Use when need to diagnose device Free time, framework/operator dispatch latency, launch latency, PYTORCH_API/CANN_API launch gaps, aclrtSynchronizeStream stalls, task queue behavior, CPU scheduling interference, GC/lock pauses, CPU affinity, or schedule-side optimization 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。

Use when diagnosing NPU + PyTorch or LLM Serving Host CPU affinity, NUMA locality, cgroup/cpuset constraints, CPU range conflicts, PyTorch/runtime threading, DataLoader, tokenizer, scheduler, vLLM-Ascend, SGLang, TTFT, TPOT, tokens/s, QPS, or multi-rank/multi-worker CPU binding issues.

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。

Guidelines for upgrading Expo SDK versions and fixing dependency issues

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。

Find App Store Connect API credentials (key ID, issuer ID, .p8 file) on the user's machine and signed-in browser session, then log in with asc CLI. Use when asc auth is needed, credentials are unknown, user says "login to App Store Connect" or "find my ASC key", or before ns-ios-deploy-app.

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。

Record product demos and walkthroughs for marketing assets. Two modes: quick screenshot-stitch demos via ply + ffmpeg, or polished Remotion compositions. Use when the user mentions product demo, demo video, walkthrough video, feature showcase, screen recording, GIF demo, product tour, onboarding video, visual tutorial, feature walkthrough, landing page video, hero video, product video, app preview video, or wants to show their product in action. Even if they just say 'show what it does', 'make a video of the app', 'I need a demo for my landing page', or 'record the app' — this is the skill. If someone has a working product and needs marketing assets that show it off, start here. Owns screen-recorded product demos and walkthroughs. For an AI-generated marketing or brand video with no real product footage, see /higgsfield-generate; for Remotion code and `remotion render` issues, see /remotion-best-practices; for stitching existing slides into an MP4, see /video-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。

Refactoring pipeline: analyzes a target file or directory for code quality issues, plans safe incremental improvements, optionally writes tests first as a safety net, implements the changes, and reviews the result. Orchestrates refactor-planner → (test-writer) → parallel-task-orchestrator → code-reviewer.

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 this skill to migrate your Jetpack Compose app to add adaptive edge-to-edge support and troubleshoot common issues. Use this skill to fix UI components (like buttons or lists) that are obscured by or overlapping with the navigation bar or status bar, fix IME insets, and fix system bar legibility.

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。

Helps developers integrate, debug, and resolve Play Engage SDK implementation issues. Use when adding Engage SDK support, generating publishing code, mapping data classes to entities, or fixing SDK-related errors.

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。