「slo」の検索結果

Refresh evaluation harnesses with live/fallback parser reliability, SLO gates, and regression checks.

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。

Safe codebase cleanup: delete AI slop, consolidate duplicates, update imports — always test-verified before committing

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。

Two-agent cleanup pattern. Implementer works freely, then a dedicated cleanup agent removes unused imports, console.logs, commented-out code, dead code, and formatting issues. Produces a diff of what was cleaned.

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 UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

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 tbh-meter problems — reader not attaching, AV/blocked state, slow calibration, missing or invalid runs. Use when debugging meter behavior or reading meter.log / live.json / raw run records / logs records (or the legacy runs.jsonl).

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 deploy, operate, secure, or scale running infrastructure — cloud architecture (multi-region, VPC, FinOps), CI/CD and deployment strategies, secrets/IAM/supply-chain security, observability and SLO alerting, SRE and incident response, Kubernetes vs ECS and autoscaling, Terraform/Pulumi/CDK, or platform engineering and DORA metrics. Also for generating runbooks, pipeline configs, Terraform modules, or Kubernetes manifests. For choosing the system's architecture or stack before it runs (monolith vs microservices, which database), use software-architect.

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 Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are slow due to repeated package installations, when rebuilds reinstall all dependencies on every code change, when image sizes are unnecessarily large, or when CI/CD pipeline builds are a bottleneck.

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。

Profile and optimize Shiny application performance using profvis, bindCache, memoise, async/promises, debounce/throttle, and ExtendedTask for long-running computations. Use when the app feels slow or unresponsive during user interaction, when server resources are exhausted under concurrent load, when specific operations create bottlenecks, or when preparing an app for production deployment with many concurrent users.

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。

Design a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

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 expensive observation from cheap decision-making in autonomous agent loops using a two-clock architecture. A fast clock accumulates data into a digest file; a slow clock reads the digest and acts only when something is pending. Idle cycles cost nothing because the action clock returns immediately after reading an empty digest. Use when building autonomous agents that must observe continuously but can only afford to act occasionally, when API or LLM costs dominate and most cycles have nothing to do, when designing cron-based agent architectures with observation and action phases, or when an existing heartbeat loop is too expensive because it calls the LLM on every tick.

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 production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.

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。

Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled 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。

Testing Vue 3 SPAs: Vitest + @vue/test-utils, RTL-style alternatives, Pinia testing via createTestingPinia, composable testing, msw for network mocks, Cypress component testing, Playwright e2e. Use this skill to: - Set up Vitest for Vue 3 with jsdom + @vue/test-utils. - Pick mount vs shallowMount. - Test components by props/emits/slots contract. - Mock Pinia stores in tests. - Test composables in isolation. - Set up Playwright or Cypress for end-to-end. Do NOT use this skill for: - General Vue conventions (see vue-conventions). - State patterns (see vue-state-management). - Form-specific patterns (see vue-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。

Use when a C++ template error needs decoding, a template needs a concept or requires-clause instead of SFINAE, or template instantiation is slowing compilation. Not for C++20 modules: use cpp-modules.

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 build or modify production-quality components, layouts, state, and pages with WCAG 2.1 AA and real content. Not for token-system design: use frontend-design-deslop.

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 builds or styles a web frontend or asks to make it not look AI-generated. Not for component-level UI work without the token system: use frontend-ui-engineering.

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 audit comments in code files and propose structural replacements or deletions with per-candidate approval. Not for deterministic commented-out-code removal: use deslop.

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 "simplify this diff" or asks for a compression pass over a change-set. Not for dead-code sweeps: use deslop.

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 Codex threads and send messages into Codex desktop-app (GUI) threads, then wait for and read their replies, so Claude can orchestrate Codex agents. Use when the user asks to message, direct, steer, start, check on, or hand work to a Codex thread or agent (often given as a thread ID like 01a10323-9edd-...), or to run Codex as a sub-agent.

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。

Enforce the anti-slop contract when duplicate helpers, fake modularization, or oversized-file pressure show up.

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 slice shows duplicate helpers, fake modularization, oversized-file pressure, or AI-shaped code slop that needs explicit cleanup discipline.

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。

Speed up Rust development iteration when `cargo build --release` takes 10+ minutes even for one-line edits. Use when: (1) every release rebuild takes minutes despite tiny edits, (2) Cargo.toml has `lto = "fat"` and/or `codegen-units = 1` in `[profile.release]`, (3) you want a production- shaped build for testing without paying the LTO cost on every iteration, (4) you suspect cargo is re-linking the whole binary instead of doing incremental work, (5) developing rfdb/grafema-orchestrator/large Rust binaries where full LTO is enabled for shipped builds. Adds a `fast` profile that inherits release but disables LTO, raises codegen-units, enables incremental compilation — first build still slow because it populates a fresh `target/fast/` dep cache, but every subsequent rebuild drops from ~13 min to ~13 s (≈60×).

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。