「sel」の検索結果

Use when writing KUnit tests, adding kselftest cases, fuzzing syscalls with syzkaller and kcov, running LTP, or wiring CI for a kernel patch.

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 Cortex-M NVIC ISRs, configuring priorities, handling HardFault, tail-chaining, or measuring interrupt latency. Not for the vector table itself: use baremetal-startup.

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 configuring ADC sampling time, DMA-driven ADC, calibration, or DAC channel setup on bare-metal MCUs. Not for the DMA stream itself: use dma-baremetal.

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 reading GCC or Clang x86-64 assembly, writing inline asm, decoding AT&T syntax, or applying System V AMD64 register rules. Not for SIMD intrinsic selection: use simd-intrinsics.

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 reading llc output, tracing IR through legalization and instruction selection, or scoping a new LLVM target. Not for IR-level passes: use llvm-ir-and-passes.

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 planning an end-to-end fuzzing program for a project: engine and target selection, corpus management, and CI or nightly wiring. Not for harness design: use fuzz-harness-writing. Not for engine operation or triage: use libfuzzer. Not for sanitizer flag reference: use sanitizers.

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Use when the user wants to batch-close resolved or outdated tracker items. The agent never closes tracker items itself. Not for individual closure or items still under active work.

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 /design-variants generates distinct design directions and a gallery for selection. Not for one polished artifact: use polished-web-prototype. Not for token-system picking: use 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。

Publish one prepared Agent evidence packet as an additive Issue comment, including historical or closed Issues, under exact current authorization. Use after read-only Issue inspection and separately authorized evidence preparation. Do not reproduce, select work, upload assets, edit human text, claim, review, close, or change Issue metadata.

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。

Freeze one eligible Proto UI autonomous-maintenance candidate into a bounded mission packet and lease. Use before observation when a current request or governed queue supplies scope, oracle, baseline, capability, risk, budget, completion, and stop conditions. Do not observe, verify, repair, or invent a mission.

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。

Run Proto UI's dynamic comprehension assessment and derive an unsigned local task-fit result. Use when an Agent needs review calibration or a fresh autonomous task and review ceiling. Do not use a self-result as identity, permission, or acceptance 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。

Establish Proto UI repository state, live contributor authority, Agent comprehension scope, task risk, and authorization before work begins. Use at the start of a development session, before autonomous task selection, after a material repository update, or when permission or assessment state may have changed.

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。

Release one current Proto UI work-item claim when it expired, became invalid, or the contributor stopped. Use only for the contributor's own recorded claim and only when the exact reversible GitHub mutation is authorized. Do not select replacement work, change readiness, or release another contributor's claim.

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。

Select, run, and report proportional Proto UI validation for a completed change. Use before review, handoff, commit, or pull request updates, and after resolving validation failures. Cover focused evidence first, then affected graph, types, docs, packaging, consumers, release, or repository checks according to risk.

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。

Fix Playwright automation failures against code-server (VS Code in browser). Use when: (1) trust dialog blocks all clicks — "monaco-dialog-modal-block intercepts pointer events", (2) button:has-text() finds wrong buttons behind modal dialog, (3) keyboard shortcuts don't work — Meta vs Control inconsistency, (4) VS Code extension activity bar icon not found by aria-label, (5) panels show placeholder text despite extension being "Connected". Covers trust dialog dismissal, keyboard shortcut hybrid mode, extension panel selectors, and database connection verification for Grafema extension.

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 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。

Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.

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。

Creates interactive HTML playgrounds — self-contained single-file explorers that let users configure something visually through controls, see a live preview, and copy out a prompt. Use when the user asks to make a playground, explorer, or interactive tool for a topic.

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。

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。

Use when researching Claude Code or Codex upstream releases, selecting adaptations, or preparing Harness upgrades. Local-only; not for distribution.

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 idiomatic application code with the ClickHouse Node.js client (`@clickhouse/client`). Use this skill whenever a user is *building* against the Node.js client - configuring the client, pinging, inserting rows in JSON or raw formats, selecting and parsing results, binding query parameters, managing sessions and temporary tables, working with data types or customizing JSON parsing. Do NOT use for browser/Web client 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。