「reliability」の検索結果

Evaluate Jacobian reliability using recently resolved conjectures as held-out probes.

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。

Detect test smells, overmocking, flaky tests, and coverage issues. Analyze test effectiveness, maintainability, and reliability. Use when reviewing tests or improving test quality.

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。

Monitor cloud infrastructure and applications using metrics, logs, and traces to provide real-time observability into performance, health, and reliability. Use when the user requests cloud monitoring or provides relevant inputs for this workflow.

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 reproducible evaluations for AI agents with representative task sets, explicit rubrics, appropriate graders, baselines, regression gates, and failure analysis. Use when defining agent quality, comparing prompts or models, validating a release, measuring tool-use reliability, investigating regressions, or deciding whether an agent is ready for production.

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。

Research npm packages — download stats, dependencies, maintainers, version history, and security advisories. Useful for technology due diligence, dependency auditing, and evaluating package reliability before adoption.

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。

Think and work like an expert MEMS Engineer. Use when a task calls for MEMS Engineer judgment. Reasons from scale-dependent mechanics, squeeze-film damping, and electrostatic pull-in through DRIE Bosch/surface micromachining, CoventorMP/COMSOL, foundry PDKs, LDV/WLI metrology, and AEC-Q103 qual while treating release stiction, DRIE scallop bias, package-stress offset drift, and functional-WLT-vs-reliability gaps as first-class failure modes.

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。

Think and work like an expert Electronic Materials Engineer. Use when a task calls for Electronic Materials Engineer judgment. Reasons from band alignment, defect chemistry, and process–structure–property links; correlates Hall, C–V (Dit), XRD/RSM, SIMS, and ALD/MOCVD/sputtering recipes while treating dopant activation vs. chemical dose, high-κ trap charging, and reliability (NBTI/TDDB) as first-class failure modes.

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。

Think and work like an expert Biomedical Imaging Scientist. Use when a task calls for Biomedical Imaging Scientist judgment. Reasons from contrast mechanisms, the resolution-SNR-scan-time triangle, and measurement reliability through DICOM/BIDS pipelines, QIBA profiles, phantom QC (ACR, NEMA IQ, Catphan), and blinded central reads (RECIST, RANO, PERCIST) while treating motion, partial volume effects, and cross-scanner harmonization drift as first-class failure modes.

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。

Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.

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。

Runtime per-test healing with evidence: multi-attribute selector healing, environment-aware diagnosis, flake classification, quarantine management, and confidence-scored auto-repair. Goes beyond simple locator fallbacks to cover action-level healing, data healing, and observable repair workflows. Use when: "flaky test," "test stability," "self-healing locator," "broken locator recovery," "unreliable test," "quarantine flaky test." Not for: bulk regenerating selectors after a planned UI refactor — use selector-drift-recovery (this skill heals ONE test at runtime; that one rewrites many tests offline). Not for: classifying/clustering CI failures into bug reports — use ai-bug-triage. Related: playwright-automation, selector-drift-recovery, ci-cd-integration, qa-metrics, ai-bug-triage.

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。

Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-reliability.

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 EXISTING test code for quality, smells, and testability issues. Detects test smells across six dimensions — readability, reliability, diagnostic value, design, AI-generated, and coverage — analyzes testability of application code, and backs the qualitative smells with mutation testing. Use when: "review my tests," "test quality audit," "test smells," "testability analysis," "are these tests any good." Not for: generating new tests — use `ai-test-generation`. Not for: testing AI features in your product — use `ai-system-testing`. Related: unit-testing, shift-left-testing, coverage-analysis, ai-test-generation.

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。

Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day planning, and progressive chaos adoption. Use when: "chaos engineering," "fault injection," "resilience test," "game day," "failure recovery," "system reliability," "blast radius." Not for: safe rollout flags/canary/dark launch during a release — use testing-in-production; designing new tests from production telemetry — use observability-driven-testing. Related: testing-in-production, observability-driven-testing, performance-testing, release-readiness, test-environments.

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。

Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-context.

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。

Produce a multi-quarter QA strategy document. Covers scope, risk-based prioritization, test levels (unit/integration/E2E), pyramid analysis, entry/exit criteria, quality KPIs, tool selection rationale, CI scaling levers, and timeline planning. Output is an actionable strategy document, not a shelf document. Use when: "test strategy," "QA strategy doc," "testing approach," "QA roadmap," "multi-quarter QA direction." Not for: a single-sprint or single-release plan — use test-planning. Not for: identifying which areas carry the most risk — use risk-based-testing first. Related: risk-based-testing, qa-metrics, release-readiness, test-planning, test-reliability.

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 escaped defects and test suite health through blameless postmortems. Covers bug pattern analysis, test suite health reviews, 5 Whys root cause analysis, process improvement cycles, and postmortem/retro meeting templates with action item tracking. Use when: "QA retro," "escaped bugs," "postmortem," "quality incident," "defect analysis," "improvement cycle." Not for: live release go/no-go decisions — use release-readiness. Not for ongoing metric dashboards — use qa-metrics. Not for reviewing existing test code quality — use ai-qa-review. Related: qa-metrics, test-reliability, test-strategy.

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。

Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not for: designing new tests from production telemetry — use observability-driven-testing. Related: qa-metrics, qa-dashboard, ci-cd-integration, qa-project-context.

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。

Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.

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。

Site reliability specialist for Prometheus metrics, distributed tracing, alerting strategies, and SLO designUse when "observability, monitoring, prometheus, grafana, alerting, slo, sli, metrics, tracing, logging, on-call, incident, observability, prometheus, grafana, tracing, jaeger, alerting, slo, sli, metrics, logging, sre, ml-memory" mentioned.

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。

Production incident response - from detection through resolution to post-mortem. Effective communication, systematic investigation, and blameless learning from failuresUse when "incident, outage, production issue, site down, on-call, post-mortem, war room, severity, pages, alerts, rollback, incident, outage, on-call, post-mortem, production, reliability, SRE, communication" mentioned.

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。

World-class DevOps engineering - cloud architecture, CI/CD pipelines, infrastructure as code, and the battle scars from keeping production running at 3amUse when "devops, infrastructure, deployment, ci/cd, docker, kubernetes, aws, gcp, azure, terraform, cloudflare, vercel, monitoring, alerting, pipeline, container, scaling, downtime, incident, sre, devops, infrastructure, cloud, ci-cd, monitoring, reliability, sre, containers" mentioned.

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。

World-class backend engineering - distributed systems, database architecture, API design, and the battle scars from scaling systems that handle millions of requestsUse when "backend, api, database, postgres, mysql, mongodb, redis, graphql, rest, authentication, authorization, caching, queue, background job, webhook, migration, transaction, n+1, rate limit, server, node.js, python, go, backend, api, database, architecture, performance, reliability, security" mentioned.

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Elixir is a functional language on the Erlang VM (BEAM) for concurrent, fault-tolerant and distributed systems. Use when someone asks to "write Elixir", "build a Phoenix app", "Phoenix LiveView", "GenServer", "supervision tree", "Ecto schema or changeset", "mix project", or needs lightweight processes, "let it crash" reliability and real-time web UIs.

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。

Multi-Agent Optimization Toolkit workflow skill. Use this skill when the user needs Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。