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概要と使いどころ
Map test coverage to GDD critical paths, identify fixed bugs without regression tests, flag coverage drift from new features, and maintain tests/regression-suite.md. Run after implementing a bug fix or before a release gate.
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。
When the user wants help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests). Also use when the user mentions 'PR,' 'public relations,' 'press,' 'press release,' 'press coverage,' 'media outreach,' 'pitch a journalist,' 'get featured,' 'media list,' 'media kit,' 'press kit,' 'newsjacking,' 'news hijack,' 'HARO,' 'Qwoted,' 'Featured,' 'Help A Reporter,' 'reporter request,' 'tech press,' 'TechCrunch,' 'earned media,' 'thought leadership placement,' 'op-ed,' 'guest article,' 'press contacts,' or 'how do I get press.' Use this for earned media work — finding journalists, pitching stories, newsjacking, and responding to press requests. For startup/SaaS/AI directory submissions, see directory-submissions. For product launches, see launch. For social-media engagement, see social. For cold-email outreach to prospects, see cold-email.
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。
Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.
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 execution reference: framework detection (pytest/jest/vitest/go/cargo/junit) and correct run/coverage commands, plus failure-analysis steps. Use when running tests, analyzing test failures, or verifying coverage after code 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 modifying domain/models/, domain/services/, adaptor/llm/, or any business logic involving insurance terms, coverages, or risk rules. Also use when adding new fields, endorsements, or coverage types.
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。
Insurance policy analysis, claims evaluation, coverage assessment, and risk management for individuals and businesses
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。
Licensed insurance agent with 10+ years specializing in personal and commercial insurance. Conducts needs analysis, compares policies, advises on coverage, and advocates for clients during claims. Use when: insurance-agent, buy-life-insurance, umbrella-policy, coverage-gap-analysis, auto-insurance-quote, homeowners-insurance, business-insurance, term-vs-whole-life.
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。
Expert insurance claim adjuster with 15+ years in property/casualty. Specializes in coverage analysis, damage quantification (RC/ACV), liability determination, fraud detection, and settlement negotiation. Use when: insurance claim, damage assessment, coverage dispute, liability analysis, fraud investigation, claim settlement.
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。
USAP agent skill for Cyber Insurance. Assess cyber insurance coverage adequacy, identify coverage gaps, maintain claim-readiness evidence, and support renewal applications.
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。
Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy. Covers threat landscape mapping, asset valuation, loss event frequency and magnitude estimation, annualized loss expectancy calculation, control gap analysis with ROI ranking, residual risk assessment, and insurance policy gap modeling at 90th/95th/99th percentile loss scenarios. Use when building risk registers, preparing board-level risk dashboards, evaluating security investment priorities, assessing cyber insurance coverage, or auditing any organization's risk quantification maturity per NIST RMF, ISO 27005, or FAIR standards.
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。
Structures cyber insurance evaluation with coverage assessment, limit adequacy, and claims scenario analysis. Use when evaluating cyber coverage, analyzing policy terms, or assessing cyber insurance adequacy.
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。
Audit or refactor a design token system for color — naming, structure, and coverage. Use when asked to "refactor our color tokens", "fix color token naming", or "improve token coverage for color".
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。
Survey documentation coverage across an API or SDK — find undocumented endpoints and gaps. Use when asked "what is undocumented", "find docs coverage gaps", or "survey our API documentation".
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。
Map current AI safety controls — filter inventory, coverage gaps, latency impact, incident history. Use when asked "what AI safety controls do we have", "find guardrail coverage gaps", or "map our filters".
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 reservation and savings plan strategy — commitment level, term, and coverage targets. Use when asked "should we buy reserved instances", "design a savings plan strategy", or "what commitment coverage do we need".
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。
Audit existing eval coverage — gaps, metric validity, benchmark leakage, dataset freshness. Use when asked "what eval coverage do we have", "audit our evals", or "check for benchmark leakage".
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。
Audit embedding infrastructure — model drift, index freshness, query latency, coverage gaps. Use when asked to "audit our embeddings", "is our index stale", or "find embedding coverage gaps".
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。
Audit existing ML monitoring — find gaps in drift coverage and missing alerts. Use when asked to "audit our ML monitoring", "are our models monitored", or "find drift coverage gaps".
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。
Survey all user-facing strings in a codebase — map coverage and find gaps. Use when asked "what user-facing strings do we have", "map our copy coverage", or "find hardcoded strings".
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。
Guides pytest test architecture for Python 3.11+ using behavioral contracts, risk, and maintenance-adjusted value. Use when choosing unit/integration/property/e2e boundaries, fixture strategy, coverage measurement, or mutation testing. Preserves existing project gates but does not invent test-pyramid ratios, coverage percentages, mutation-score targets, or tests for implementation detail.
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。
Pytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based strategies.
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 pytest test effectiveness against authoritative contracts, relevant faults, behavior-preserving refactors, realistic boundaries, isolation, and diagnostics. Use for test-quality audits, coverage-gap reviews, regression-test changes, or mocking reviews; preserve existing project gates rather than inventing coverage targets.
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 whether an implementation plan can achieve its stated outcome before execution. Use to check requirement coverage, task contracts, dependencies, data/artifact flow, testability, ownership, impact coverage, and executable ordering without checking whether implementation already exists.
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, create, run, monitor, and maintain Vapi Simulations for assistants and squads. Use for turning plain-language requirements into a coverage plan, simulation personalities, scenarios, structured-output success criteria, simulations, suites, extending an existing suite, chat or voice runs, tool mocks, target variables, lifecycle webhooks, regression coverage, launch readiness, CI quality gates, run-result analysis, and simulation API validation errors. Do not use for fixed-turn mock-conversation Evals unless the user is deciding between Evals and Simulations.
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。