本文へ移動
cccskills

「acceptance」の検索結果

478 件 ・ 関連度順

概要と使いどころ

Creates clear, testable specifications from feature descriptions with user stories. Use when starting a new feature and needing a spec before planning.

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。

athola/claude-night-market3412026年10月10日 更新

Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.

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。

athola/claude-night-market3412026年10月10日 更新

Generates customized client onboarding checklists with phased tasks, ownership assignments, dependencies, acceptance criteria, and email templates. Adapts to consulting, SaaS, or agency engagement models.

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。

OneWave-AI/claude-skills3402026年10月2日 更新

Use when choosing where to submit a manuscript. Matches the abstract against curated journal profiles and returns ranked picks with scope fit, AI-disclosure policy, an acceptance-readiness pre-flight and a reject-fallback cascade. Impact and APC figures may be stale.

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。

Aperivue/medsci-skills3372026年10月12日 更新

Structures risk mitigation planning and residual risk tracking for Data Protection Impact Assessments under GDPR Article 35(7)(d). Covers mitigation measure identification, implementation tracking, residual risk acceptance, and Art. 36 prior consultation triggers. Keywords: DPIA mitigation, risk treatment, residual risk, Art. 35(7)(d), safeguards, mitigation tracking, prior consultation.

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。

mukul975/Privacy-Data-Protection-Skills3032026年3月17日 更新

Methodology for auditing A/B testing of consent banners to ensure compliance with equal ease of acceptance and rejection. Covers CNIL enforcement patterns including the EUR 150M Google fine, dark pattern detection methodology, manipulative design identification, and regulatory-compliant experimentation boundaries.

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。

mukul975/Privacy-Data-Protection-Skills3032026年3月17日 更新

Compares PIA/DPIA methodologies: CNIL PIA tool, ICO DPIA template, NIST Privacy Framework, and ISO 29134. Provides methodology selection criteria based on regulatory jurisdiction, organisation maturity, processing complexity, and resource availability. Covers regulatory acceptance, tool features, and cross-methodology mapping. Keywords: PIA methodology, CNIL, ICO, NIST Privacy Framework, ISO 29134, DPIA comparison, assessment.

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。

mukul975/Privacy-Data-Protection-Skills3032026年3月17日 更新

Review an implemented RFC in a fresh context against its acceptance criteria, RULES.md and the test plan, and save the review to reviews/.

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。

nurettincoban/ai-prd-workflow3002026年10月9日 更新

Turn PRD.md into FEATURES.md: permanent feature IDs, MoSCoW priorities, acceptance criteria and the PRD requirement each feature comes from.

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。

nurettincoban/ai-prd-workflow3002026年10月9日 更新

Implement one RFC: check its predecessors, present a plan for approval, write the code, then demonstrate every acceptance criterion.

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。

nurettincoban/ai-prd-workflow3002026年10月9日 更新

pl-audit

無料

PL (Project Lead) role sub-skill for acceptance and close-audit. Loaded ONLY through the pl core routing table; NEVER auto-load from context, never invoke directly.

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。

sno-ai/sno-station-skills2882026年10月13日 更新

PRD writing and product definition expert. Use when writing PRDs, user stories, acceptance criteria, or prioritizing features. Covers RICE/MoSCoW frameworks, agile requirements, and specification best practices.

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。

majiayu000/spellbook2872026年10月8日 更新

Master requirements gathering, user story writing, acceptance criteria definition, and scope management. Transform insights into clear, actionable specifications.

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。

nicepkg/ai-workflow2852026年1月20日 更新

Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.

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。

testdouble/han2832026年10月1日 更新

Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying assumptions and implicit dependencies, or (6) Preparing requirements for design, implementation, or verification. Operates interactively: analyze → ask clarifying questions → refine based on responses.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.

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。

ArabelaTso/Skills-4-SE2532026年8月21日 更新

Review code changes adversarially using parallel review layers (Blind Hunter, Edge Case Hunter, Acceptance Auditor) with structured triage into actionable categories. Use when the user says "run code review" or "review this 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。

bmad-code-org/bmad-module-game-dev-studio2512026年9月25日 更新

Write comprehensive Product Requirements Documents with user stories, acceptance criteria, technical specifications, wireframe descriptions, and prioritization frameworks (RICE, MoSCoW). Create clear specifications for product teams.

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。

w95/awesome-claude-corporate-skills2462026年2月27日 更新

Launch and drive an isolated World of Warcraft 1.12.1 client against a local Thistle Tea server, including keyboard input, left/right clicks, camera drags, screenshots, real instance entry, log observation, and Tidewave runtime probes. Use for real-client gameplay acceptance, client-sensitive protocol or movement verification, reproducing live bugs, checking visibility and instance isolation, or validating a scripted content chain beyond automated tests.

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。

pikdum/thistle_tea2382026年10月11日 更新

pm-prd

無料

Генерирует структурированный PRD (Product Requirements Document) с шаблонами под тип продукта (B2C / B2B / внутренний инструмент / платформа) — фон, цели, детальный дизайн фич, acceptance criteria в Given-When-Then, аналитика и 10-пунктовый чеклист качества. User-invoked only — do NOT auto-trigger. Triggers on /pm-prd, "сделай PRD", "напиши PRD", "продуктовые требования", "make a PRD", "write a PRD", "draft requirements doc".

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。

serejaris/personal-corp-os2292026年10月8日 更新

Inspect an unfamiliar repository, turn a focused Markdown behavior scenario into a deterministic test in the repository's native test stack, run it, and preserve traceability between intent and code. Use when asked to add scenario tests, compile acceptance criteria or Given/When/Then Markdown into executable tests, reproduce a user-visible regression, or convert a narrow workflow specification into stable web, API, CLI, desktop, or mobile interaction coverage. Do not use for broad exploratory journeys or agent-judged smoke tests.

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。

tamdogood/builder-essential-skills2222026年8月17日 更新

Think and work like an expert Geotechnical Engineer. Use when a task calls for Geotechnical Engineer judgment. Reasons from effective stress and LRFD/EC7 limit states through GDR/GBR/FDR deliverables, shallow and deep foundations (GEC 6/10/12), excavation support (DeepEX, LPILE), ground improvement, ASCE 7 liquefaction, observational-method triggers, and FHWA pile acceptance while treating DSC claims, setup vs. blow count, and GBR-vs-design conflation 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Construction Engineer. Use when a task calls for Construction Engineer judgment. Reasons from design intent versus means-and-methods through CPM/P6 and Last Planner scheduling, Revit/Navisworks BIM coordination, IBC Chapter 17 special inspections, ASTM C31/C39 cylinder acceptance, and ACI 318 low-break/core protocols while treating formwork collapse, honeycombing, tolerance stack-up, and schedule logic errors 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Astroparticle Physicist. Use when a task calls for Astroparticle Physicist judgment. Reasons from flux times cross section times acceptance, Poisson counting over structured backgrounds, and Cherenkov photoelectron budgets through SkyLLH unbinned likelihoods, Geant4/CORSIKA chains validated on through-going-muon and calibration samples, and Feldman-Cousins/CLs limits, while treating atmospheric-neutrino and downgoing-muon contamination, ER/NR leakage and the neutrino fog, and look-elsewhere trials 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。

K-Dense-AI/scientific-agents2052026年10月3日 更新