'acceptance' 검색 결과

Acceptance Orchestrator workflow skill. Use this skill when the user needs a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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"Apply the Technology Acceptance Model (Davis, 1989) and Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) to predict technology adoption. Use this skill when the user needs to evaluate user acceptance of a new system, diagnose adoption barriers, design interventions to improve technology uptake, or when they ask 'why aren't users adopting this', 'what drives technology acceptance', or 'how do we increase adoption rates'.".

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Write measurable acceptance criteria for requirements or user stories. Use when the user says "write acceptance criteria", "definition of done", "how do we test this", "fit criteria", "given when then", "Gherkin scenarios", "what does done look like", "testable conditions", "how will we know this works" - even if they don't explicitly say "acceptance criteria".

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기존 작업이 수용 조건을 충족하는지 필요한 만큼만 검사합니다. 현재 상태에도 유효한 결과를 재사용하고, 통과 여부와 실행하지 못한 이유를 정리한 뒤 검증을 마칩니다.

• 완료한 작업의 수용 조건 확인
• 지정한 조건만 검증
• 여전히 유효한 검증 결과 재사용

Turn a feature idea into a structured specification before coding. Review requirements, system connections, constraints, and failure scenarios, define testable acceptance criteria, and save the specification in memory for later development phases.

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• Defining requirements before building a new feature
• Writing testable acceptance criteria
• Documenting constraints and failure scenarios

Review an AI team's work against its acceptance criteria using collected evidence. Match requirements to task results or artifacts, distinguish verified facts from agent claims, and identify uncertainty or missing work before recommending completion.

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• Review evidence before closing an AI team run
• Check whether deliverables meet acceptance criteria
• Separate verified results from agent claims

Plan and document studies that assess whether an analytical procedure suits its intended use. Select the governing framework, evaluate calibration, accuracy, precision, and detection limits, and compare methods using acceptance criteria defined before data collection.

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• Planning analytical validation studies and acceptance criteria
• Evaluating calibration, accuracy, and precision
• Estimating and confirming detection and quantitation limits

Evaluate job offers by separating guaranteed pay, conditional bonuses, and estimated equity value. Compare terms, develop an evidence-based counteroffer, draft emails and call scripts, rehearse recruiter conversations, and prepare deadline extensions, acceptance, or decline messages.

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• Comparing pay and terms across job offers
• Drafting a counteroffer email
• Rehearsing a salary negotiation call

Turn a Codewhale bug or feature idea into an actionable GitHub issue with evidence, reproduction steps, and testable acceptance criteria. Check related work, select existing labels and a milestone, and return the filed issue with supporting evidence.

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• File a bug with reproduction steps and evidence
• Define testable acceptance criteria for a feature idea
• Check for duplicate issues and related pull requests

Turn a feature idea or user problem into a structured specification or product requirements document. Define goals, scope, priorities, success measures, and acceptance criteria, with phased delivery when the request is too large.

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• Turn a vague idea into a feature specification
• Define feature scope and priorities
• Set success measures and acceptance criteria

Plan features before coding by defining requirements, acceptance criteria, and scope. Validate the specification, generate starter tests from expected behaviors, and guide implementation and review so each delivered feature can be checked against its agreed requirements.

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• Define requirements before implementing a feature
• Turn acceptance criteria into starter tests
• Check specifications for missing requirements

Turn user stories and acceptance criteria into detailed test scenarios. Define objectives, starting conditions, user roles, actions, and observable results, including invalid inputs and boundary cases, so a quality assurance team can carry out the checks.

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• Writing test cases from user stories
• Preparing acceptance test scenarios
• Checking invalid inputs and boundary cases

Break a feature into job stories that describe the user's situation, motivation, and desired outcome. Add six to eight observable acceptance criteria per story, defining how success will be checked, and include links to designs or prototypes.

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• Breaking a new feature into job stories
• Writing backlog items around user situations
• Defining acceptance criteria for desired outcomes

Review a completed development task against its acceptance criteria, check differences from design and architecture documents, and prompt code review. After approval, update the task's status and identify the next story to work on.

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• Checking acceptance criteria before closing a development task
• Recording differences between implementation and design
• Remembering code review before marking work complete

Break a large game development feature into implementation tasks with clear acceptance criteria. Each task carries relevant requirements and design decisions, with test specifications added when the selected review mode includes a QA review.

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• Break a game feature into implementation tasks
• Carry requirements and design decisions into task files
• Define acceptance criteria and test specifications

Use this design reference when planning centrally managed rules for outbound network traffic from a sandbox, an isolated execution environment. It covers design and acceptance gates, but does not itself enforce network restrictions.

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• Planning centrally managed sandbox outbound network rules
• Reviewing acceptance gates before implementation
• Consulting the gateway reference before adding network controls

Turn rough feature ideas into a clear SPEC.md through focused questions. Define target users, business rules, current scope, and acceptance criteria based on observable results, giving developers or AI agents concrete requirements to implement.

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• Turning rough feature ideas into requirements
• Defining observable acceptance criteria
• Clarifying current scope and exclusions

Translate user needs into concise stories that explain who benefits, what they want, and why. Add Gherkin acceptance criteria—preconditions, an action, and an expected result—to support development discussions and testable definitions of success.

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• Turning requirements into user stories
• Defining testable acceptance criteria before development
• Preparing stories for backlog refinement and sprint planning

Compare a Linear issue and its acceptance criteria with implementation evidence. Identify gaps, retain links to tests and pull requests, and update progress only when the relevant implementation, review, or deployment milestone is supported.

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• Comparing acceptance criteria with implementation evidence
• Checking gaps before updating a Linear issue
• Adding links to pull requests, tests, and releases

Turn a vague development idea into clear goals, constraints, and acceptance criteria through a guided interview. It checks unresolved decisions and confirms the agreed goal before moving toward a Seed, the requirements document used by Ouroboros.

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• Clarifying a vague idea before development
• Defining completion criteria for a new feature
• Agreeing on scope and constraints

Generate a report with predictable output for acceptance tests of disposable executors, or temporary task runners. Retrieve agent settings, run the supplied report script with specified arguments, and publish the resulting file to S3.

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• Generating a report for disposable executor acceptance tests
• Checking report output with specified arguments
• Publishing a verification report to S3

Develop and fix Nexent features by connecting written specifications, acceptance criteria, implementation, and verification evidence. Plan unit tests and appropriate staged checks, maintain their links to requirements, and fill confirmed test gaps after development.

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• Planning and implementing features from acceptance criteria
• Fixing bugs using existing specifications and tests
• Refactoring while preserving required behavior

Turn ready project tasks into clear instructions for AI workers, with defined ownership, deliverables, acceptance criteria, and reporting rules. Handle assignment notifications and check submitted results before passing them to the project management workflow for acceptance.

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• Writing instructions for ready project tasks
• Defining deliverables and acceptance criteria
• Checking submitted worker results

Plan how multiple agents should work together. Choose between dependency-based tasks and repeated work cycles, define ownership and acceptance criteria, identify safe parallel work, and decide how to handle results, interruptions, or revised goals.

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• Dividing work among multiple agents
• Choosing dependency plans or repeated cycles
• Defining result acceptance criteria