「acceptance」の検索結果

Create product backlog items in Why-What-Acceptance format — independent, valuable, testable items with strategic context. Use when writing structured backlog items, breaking features into work items, or using the WWA format.

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Create comprehensive test scenarios from user stories with test objectives, starting conditions, user roles, step-by-step actions, and expected outcomes. Use when writing QA test cases, creating test plans, defining acceptance tests, or preparing for feature validation.

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End-of-story completion review — verifies each acceptance criterion, checks GDD/ADR deviations, prompts code review, updates status.

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Is a story implementation-ready? Checks clear acceptance criteria, open questions, ADR refs. READY/NEEDS WORK/BLOCKED/NOT ASSESSED.

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Break one epic into implementable stories embedding TR-ID, ADR guidance, acceptance criteria. Reads the control manifest. After /create-epics.

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Plan or divide a named NemoClaw issue into independently useful changes with acceptance evidence. Use for planning requests before implementation.

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Design and acceptance gates for centrally enforcing sandbox outbound network policy.

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Hardens LifeOS tests via property/mutation testing. USE WHEN harden, hardening, property test, property based testing, PBT, fast-check, mutation test, mutation testing, Stryker, CRAP score, CRAP analysis, DRY scan, jscpd, acceptance test mutation, strengthen tests, sharpen ISCs, find bugs example tests miss, universal quantified claim, shrink counterexample, what bugs am I missing, test the tests, test of the test. NOT FOR writing new feature tests (use bun test directly), grading agent output quality (use Evals), UI verification with real Chrome (use Interceptor), finding security vulnerabilities, or building new functionality.

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This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops, meta-harnesses, self-improving harnesses that mine their own failures and propose bounded edits, evolutionary or population-based search over agent scaffolds, acceptance gates for self-modifying systems, and agentic context evolution where the mechanism that produces context is versioned and evolved. Route governance of a single autonomous loop (locked surfaces, durable logs, rollback, novelty gates, approval boundaries) to harness-engineering, measurement and quality-gate design to evaluation, judge design to advanced-evaluation, and remote sandbox infrastructure to hosted-agents.

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Manage a stateful, run-directory-based proof project with Codex: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.

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Manage a stateful, run-directory-based proof project: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.

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Read before automating LinkedIn with browser_* tools. LinkedIn combines shadow DOM (#interop-outlet), strict Trusted Types CSP that silently drops innerHTML, Lexical composer, native beforeunload dialogs that hang the bridge, and aggressive spam filters — each has bitten us at least once. Verified flows for profile messaging, connection-request acceptance, feed composition, and search. Requires hive.browser-automation. Verified against logged-in production 2026-04-11.

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Structured intake — practice-area templates, cross-area issue spotting, conflict flags, and triage classification. Produces a formatted case summary the student analyzes and the professor reviews. Does NOT decide case acceptance. Use when starting a new client intake, running an intake interview, or writing up a new client's situation.

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Enrolls a project in OSS-Fuzz, Google's free continuous fuzzing service for open source, and drives it locally. Covers project.yaml, Dockerfile and build.sh setup, the helper scripts, reproducing OSS-Fuzz crash reports, and the acceptance criteria. Use when setting up continuous fuzzing for an open-source project, reproducing an OSS-Fuzz bug report, or testing an OSS-Fuzz build before submitting it.

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Publish a validated Data Analytics report or dashboard artifact through Sites. Use automatically for durable artifacts in any positively identified Work Mode when the full Sites lifecycle is callable, or in ChatGPT Desktop outside Work Mode only after an explicit Sites request or acceptance of the optional post-handoff sharing offer.

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Use when converting PM intake into a slice SPEC.md with observable acceptance outcomes, explicit scope, and advisory sibling build dependencies.

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Create user stories with Mike Cohn format and Gherkin acceptance criteria. Use when turning user needs into development-ready work with clear outcomes and testable conditions.

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Scores how completely an implementation fulfills a PRD/spec, case by case, and produces a single comparable final grade. Invoke only when explicitly named (e.g. run spec-driven-eval); do not auto-trigger. Use when benchmarking spec-driven implementations, grading acceptance criteria, evaluating whether a feature was 100% implemented, comparing multiple implementations of the same PRD, or auditing implementation and test coverage (unit and e2e) against product requirements. Do NOT use for planning or building features (use tlc-spec-driven), writing PRDs, or general code review unrelated to a spec.

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Keep a Linear issue aligned with implementation evidence, acceptance criteria, code review, and deployment state while avoiding premature completion claims.

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Run Nexent requirements and bugfixes through SPEC acceptance, traditional UT and applicable D1-D5 test design, product/test implementation, local verification, and delivery evidence. Use for features, fixes, refactors and post-development test backfill across APIs, UI, model and Agent behavior.

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Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.

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Use when a Leader must choose Project Work boundaries, owners, dependency shape, DAG vs Loop, acceptance criteria, or follow-up strategy. Do not use for Quick Task execution after the mode is already selected.

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Use before direct filesync calls, reading non-task shared files, pushing mid-task progress, or troubleshooting missing shared files. Do not use for normal task acceptance or submission; taskflow ack_task and submit_task handle lifecycle sync internally.

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Use before deciding how you should organize team work: DAG vs Loop, dependency shape, task waves, quality gates, acceptance criteria, interruption, replanning, or what to do after Worker results arrive. Always use this skill for team organization strategy before you call project-management or task-management.

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