「severity」の検索結果

Audits skills in this repo for consistency, API drift, and structural gaps. Produces a prioritized report grouped by severity (Critical/High/Medium/Low). Use when asked to "audit skills", "check the skill repo for drift", or when planning bulk skill cleanup. Read-only — does not apply fixes.

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Review open PRs two ways - default is a per-PR deep review with severity-tagged findings, inline comments, and a verdict; --survey runs a risk-tiered triage digest of what's safe to merge first

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Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews

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Platform design review critique dimensions and severity levels. Load when reviewing CI/CD pipelines, infrastructure, deployment strategies, observability, or security designs.

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Use when a brand faces a communications CRISIS or a campaign is failing in public — L1 to L5 severity classification, a first-four-hours process, response templates by type, an escalation matrix, a do-not-do list, holding statements, and a post-mortem. Trigger on 'PR crisis', 'crisis playbook', 'a complaint is going viral', 'bad reviews are spreading', 'our content caused backlash', 'we are getting attacked online'. Also use when the user forwards an angry thread and asks what to do right now. Not for — monitoring before anything blows up, see `15-social-listening-global`; diagnosing weak performance numbers, see `03-performance-eval-global`; the routine post-campaign review, see `63-campaign-retrospective-global`.

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Weekdays, heavy browser lane. Reads every support channel named in strategy/channels.md, meaning the mailbox, the helpdesk queue, the review and rating listings, the marketplace pages, and the forums where the member's products are discussed, and captures every new or changed item as one dated, sourced, severity graded line on the ticket ledger. It replies to nothing, reacts to nothing, marks nothing read or resolved, and takes no action of any kind on LinkedIn. It holds every outbound action unless you released the channel, and it never touches a credential.

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Use after /gsd-audit-uat when the user wants the findings fixed, not just listed. Classifies each issue as auto-fixable or manual and fixes the auto-fixable ones with test verification and atomic commits; --severity sets the floor.

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NIST SP 800-61r3-aligned incident triage that preserves evidence, separates analysis from authorization, and records status. Use for incident intake, severity assessment, containment readiness, or evidence preservation; not generic debugging or unscoped response.

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Designs and reviews detections from telemetry prerequisites, correlation logic, Sigma metadata, severity, status, and benign cases. Use for detection rules, Sigma review, analytic coverage, or tuning; not generic logging advice or live deployment.

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Review changed Elixir/Phoenix code read-only. Check requirements, cite evidence, deduplicate findings, and return a severity-based verdict.

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Reviews lyrics and prose for AI-written patterns (abstract noun stacking, over-explained metaphors, cliche escalation, missing idiosyncrasy, prose AI tells). Advisory Warning/Info severity — flags issues, does not block or rewrite. Use when reviewing lyrics for authenticity or before generation to catch AI-sounding language.

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Operational rubric that turns "don't make AI slop" into observable properties, severity levels, evidence requirements, and repair actions for interface design. Use as the reference rubric when building or reviewing marketing sites, product interfaces, dashboards, portfolios, or e-commerce pages, especially alongside frontend-design.

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시각 + 브랜드 일관성 리뷰. HTML/MD/JSX artifact를 받아 brand DESIGN.md 대비 typo hierarchy, 색 budget, radius scale, 컴포넌트 state, 모바일 반응형 검수. severity BLOCK/WARN/FYI + line ref 출력. 'UI 리뷰', '디자인 검토', 'DESIGN.md 대비 검수' 류 트리거.

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Incident severity classification, runbook templates, root cause analysis, and post-incident review

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Guide incident response from detection to post-mortem using SRE principles, severity classification, on-call management, blameless culture, and communication protocols. Use when setting up incident processes, designing escalation policies, or conducting post-mortems.

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Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity metrics.

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Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy patterns.

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Audit a test file or suite; produce a severity-ranked diagnostic report. ALWAYS USE for tests that verify nothing, missing/tautological assertions, swallowed/broad exceptions, flaky/order-dependent tests, duplication, or magic values. Polyglot. DO NOT USE for direct edits: writing-mstest-tests owns supplied MSTest assertions/attributes/lifecycle; code-testing owns new tests. Exclude running tests, migration, assertion metrics (assertion-quality), raw .NET coverage collection (run-tests), non-.NET coverage collection/analysis (native tooling), project-wide .NET coverage/CRAP (coverage-analysis), named-target .NET CRAP (crap-score), behavioral/pseudo-mutation gaps (test-gap-analysis), test-mix/ happy-vs-error classification and trait distributions (test-tagging), or the testsmells.org catalog (test-smell-detection).

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Analyze assertion quality, depth, variety, and false confidence in existing tests. ALWAYS USE when asked about weak, shallow, trivial, always-true, self-referential, assertion-free, presence/truthiness-only, or insufficiently diverse assertions, including MSTest, Jest, pytest, and Go. DO NOT USE for direct fixes: writing-mstest-tests owns supplied MSTest assertions; code-testing owns new cases. Use test-gap-analysis when asked whether tests would catch a production change, and test-anti-patterns for general severity-ranked audits.

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Analyze a codebase and produce a structured threat model at .turbo/threat-model.md covering assets, trust boundaries, attack surfaces with existing mitigations, attacker stories, and calibrated severity. Use when the user asks to "create a threat model", "threat model", "threat model this codebase", "security analysis", "analyze the attack surface", "what are the threats", or "identify security risks".

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Use when about to record, claim, rate the severity of, or report any security finding — before marking anything [CONFIRMED] or writing it into the report

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Query DDInter drug-drug interactions via REST API (1.7M+ interactions, 2,400+ drugs). Search by drug name/ID for severity (major/moderate/minor), mechanisms, and clinical recommendations. No auth. For FDA labeling use dailymed-database; for pharmacogenomics use clinpgx-database.

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Parse local DrugBank XML for drug info, interactions, targets, and properties. Search by ID/name/CAS, extract DDIs with severity, map targets/enzymes/transporters, compute SMILES similarity. Primary via local XML; REST API rate-limited (3k/month dev). For live bioactivity use chembl-database-bioactivity; for compound properties use pubchem-compound-search.

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Production incident response automation. Reads logs, checks recent deploys, identifies root cause, suggests fixes, drafts incident comms, creates post-mortem templates. Severity classification (SEV1-4), escalation paths, status page updates. Generates incident-report.md with timeline, root cause, impact assessment, remediation steps, and prevention measures.

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。