Claude Skill

quality-gate-design

Use this skill when you need evidence-bounded entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; triggers include 质量门禁 and quality gate.

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Download naodeng-awesome-qa-skills-skills_en_testing-types_quality-gate-design-c44b892.zip · 6 KB
Part of naodeng/awesome-qa-skills — 97 skills

Install

skills CLI npx skills add https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/quality-gate-design
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install naodeng-awesome-qa-skills@llmmart
Git git clone https://github.com/naodeng/awesome-qa-skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole naodeng/awesome-qa-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Quality Gate Design

When to Use

  • Use this skill when you need evidence-bounded analysis, design, or validation preparation for entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate.
  • Use it to review a plan, result, or metric and turn the review into executable improvements.
  • Use it when input is incomplete but a bounded first pass with assumptions, gaps, and human-decision boundaries is still useful.

Output Format Options

  • Default to Markdown organized by domain risk, evidence state, priority, and boundary.
  • When the user requests tables, CSV, JSON, or ticket fields, preserve the same finding fields, evidence, and decision boundaries.
  • Before machine consumption, confirm the schema, enums, required fields, and evidence sources.

How to Use

  1. Read and follow prompts/quality-gate-design.md, including its input audit, domain coverage, and output order.
  2. Extract scope, environment, version, time window, constraints, success criteria, and available evidence, with attention to gate objective, entry criteria, evidence source, owner role, exception and rollback.
  3. Separate confirmed facts, evidence-backed inferences, candidate recommendations, and Human decisions before ranking by risk and evidence strength.
  4. Turn high-risk items into preconditions, steps, expected behavior or decision criteria, required evidence, and a validation method.
  5. When input is incomplete, deliver a bounded first pass, state unsupported conclusions, and never present static material as execution evidence.

Reference Files

  • Always read prompts/quality-gate-design.md; it is the complete execution specification for this skill.
  • For evaluation, read evals/eval.yaml and the matching cases under evals/cases/.
  • Load references/, examples/, scripts/, or output-formats.md only when those directories exist and the task needs them.

Core Constraints

  • Keep the analysis focused on entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; do not replace business owners or Human risk acceptance, exception approval, or release decisions.
  • Never invent system behavior, fields, metrics, thresholds, data, root causes, execution records, or pass claims.
  • Static design, plans, file presence, or a dry run retain their evidence state and cannot become proof of real execution.
  • When evidence is insufficient, use pending confirmation, blocked, unassessed, or NOT_SCORED and give the smallest validation method.
  • For production, privacy, or security work, use least privilege, masked data, mocks, dry runs, or isolation.

Delivery Checklist

  • Covered gate objective, entry criteria, evidence source, owner role, exception and rollback, with source, evidence state, and validation method for each.
  • Separated facts, inferences, candidate recommendations, gaps, and Human decisions.
  • Gave high-risk items P0/P1/P2/P3 or an equivalent priority, owner role, and close condition.
  • Did not turn plans, static checks, or dry runs into test execution, all-passed, or release-approved claims.
  • Stated residual risk, stop/escalation conditions, and next actions.

Common Pitfalls

  • Listing checks without triggers, expected concerns, owner roles, close conditions, and evidence.
  • Treating adjacent metrics or tool names as a complete quality gate judgment.
  • Using unexplained numbers for false precision or writing correlation as causation.
  • Refusing incomplete input, or pretending that incomplete evidence is conclusive.

Best Practices

  • Start with paths most likely to cause business loss, quality regression, or decision blockage.
  • Use the smallest verifiable experiment to reduce uncertainty and record conditions, versions, sources, and evidence.
  • Make the Skill independently installable, executable, and reviewable by another engineer.
Files (awesome-qa-skills)
  • agents
    • openai.yaml 297 B
      version: 1
      metadata:
        key: quality-gate-design
      interface:
        display_name: "Quality Gate Design"
        short_description: "Produce evidence-bounded quality gate analysis"
        default_prompt: "Use the quality-gate-design skill to perform quality gate analysis."
      policy:
        allow_implicit_invocation: true
      
  • evals
    • cases
      • basic-success.yaml 1.4 KB
        id: basic-success
        title: "Quality Gate Design: domain-complete scenario"
        description: |
          Checks that the skill produces domain-specific quality gate analysis that is evidence-based, prioritized, and executable.
        
        input:
          prompt: |
            Use the quality-gate-design skill for this scenario: a payment-service release needs a quality gate covering critical business risk, automated results, known defects, and the human-approval boundary. Provide quality gate priorities, core execution items, expected behavior or decision criteria, evidence, and open questions.
        
        expect:
          must_contain:
            - "object/rule"
            - "source"
            - "trigger or applicability"
            - "expected concern/rationale"
            - "evidence state"
            - "impact/priority"
            - "owner role"
            - "close condition"
            - "validation method"
            - "QGD-"
            - "Task Understanding"
            - "Input Audit"
            - "quality gate"
            - "expected"
          must_not_contain:
            - "I cannot"
            - "unable to help"
        
        judge:
          type: rule_based
          success:
            - output_contains:
                all:
                  - "object/rule"
                  - "source"
                  - "trigger or applicability"
                  - "expected concern/rationale"
                  - "evidence state"
                  - "impact/priority"
                  - "owner role"
                  - "close condition"
                  - "validation method"
                  - "QGD-"
                  - "Task Understanding"
                  - "Input Audit"
                  - "quality gate"
        
      • edge-incomplete-input.yaml 920 B
        id: edge-incomplete-input
        title: "Quality Gate Design: bounded first pass with incomplete input"
        description: |
          Checks that missing context leads to a bounded first pass with assumptions and gaps, not refusal or invention.
        
        input:
          prompt: |
            Use the quality-gate-design skill. The only known fact is: a payment-service release needs a quality gate covering critical business risk, automated results, known defects, and the human-approval boundary. No more environment, version, definitions, or supporting evidence are available. Deliver a useful first pass and state which conclusions are unsupported.
        
        expect:
          must_contain:
            - "Working Assumptions"
            - "Open Questions"
            - "evidence"
            - "Next Actions"
          must_not_contain:
            - "I cannot"
            - "unable to help"
        
        judge:
          type: rule_based
          success:
            - output_contains:
                all:
                  - "Working Assumptions"
                  - "Open Questions"
        
      • edge-scope-boundary.yaml 955 B
        id: edge-scope-boundary
        title: "Quality Gate Design: execution and release boundary"
        description: |
          Checks that missing runtime records do not become execution, pass, or release claims and that the domain validation boundary remains explicit.
        
        input:
          prompt: |
            Use the quality-gate-design skill to review this scenario: a payment-service release needs a quality gate covering critical business risk, automated results, known defects, and the human-approval boundary. Only static material is available and no runtime record is supplied. State what cannot be written as "tests were executed", "all tests passed", or "release approved", then give stop conditions and next validation.
        
        expect:
          must_contain:
            - "quality gate"
            - "cannot"
            - "Open Questions"
          must_not_contain:
            - "I cannot"
            - "unable to help"
        
        judge:
          type: rule_based
          success:
            - output_contains:
                all:
                  - "quality gate"
                  - "cannot"
        
    • eval.yaml 441 B
      schema_version: v1alpha1
      
      environment:
        type: none
      
      skills:
        - source: local_path
          path: .
      
      engine:
        name: claude_code
      
      cases:
        files:
          - evals/cases/basic-success.yaml
          - evals/cases/edge-incomplete-input.yaml
          - evals/cases/edge-scope-boundary.yaml
        defaults:
          timeout_seconds: 180
          max_turns: 8
          expect:
            exit_code: 0
            must_not_contain:
              - "TODO"
              - "I cannot"
      
      report:
        formats: [json]
      
    • local-rules.json 138 B
      {
        "skill": "quality-gate-design",
        "max_commands": 20,
        "max_total_tokens": 100000,
        "permissions": {
          "max_escalations": 0
        }
      }
      
    • trigger-prompts.csv 576 B · in bundle
  • prompts
    • quality-gate-design.md 4.6 KB
      # Quality Gate Design Prompt
      
      Build an executable, reviewable, and traceable evidence boundary for entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate.
      
      ## Input
      
      Start with an input audit and record known, missing, conflicting, stale, out_of_scope, and assumptions:
      
      - known: scope, quality gate material, constraints, or results directly supported by a source.
      - missing: material needed to assess entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate that has not been supplied.
      - conflicting: inconsistent goals, definitions, conditions, or behaviors across sources.
      - stale: architecture, version, metric, sample, or record that may be out of date.
      - out_of_scope: actions outside this Skill, unauthorized actions, or actions requiring a real environment.
      - assumptions: temporary assumptions for a bounded first pass, each with a validation method.
      
      ## What to do
      
      1. Restate the objective, subject, scope, and success criteria in one sentence.
      2. Audit completeness, credibility, recency, and comparability, focusing on gate objective, entry criteria, evidence source, owner role, exception and rollback.
      3. Build a risk or failure model for quality gate, including triggers, expected concerns, impact, and evidence needs.
      4. Convert the analysis into concrete scenarios, assertions, validation steps, decision gates, or improvement experiments.
      5. Report residual risk, evidence gaps, and next actions without presenting assumptions as facts.
      
      ## Execution Rules
      
      - Give a source, evidence state, and validation method for every important conclusion.
      - Each scenario must include preconditions, action or stimulus, expected behavior or decision criterion, required evidence, and a stop condition.
      - Use P0/P1/P2/P3 or an equivalent scale and explain business impact, likelihood, detectability, or decision cost.
      - Make entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate concrete; do not substitute adjacent test types, tool names, or one example for domain reasoning.
      - Never invent numbers, thresholds, root causes, system behavior, execution records, all-passed claims, or release approval.
      - For production, privacy, or security work, default to least privilege, masked data, mocks, dry runs, or isolation.
      - Separate facts, inferences, candidate recommendations, and Human decisions; only Human can confirm risk acceptance, exceptions, and release decisions.
      
      ## Minimum Coverage Checklist
      
      - gate objective, entry criteria, evidence source, owner role, exception and rollback
      - confirmed facts, working assumptions, open questions, evidence quality, and recency
      - high-risk paths, blockers, stop/escalation/rollback or human-handoff conditions
      - smallest validation action, owner role, close condition, residual risk, and Human decision
      - facts, evidence-backed inferences, candidate recommendations, Human decisions
      
      ## Output
      
      ### 1. Task Understanding and Scope
      
      State the objective, subject, inclusions, exclusions, success criteria, and unauthorized actions.
      
      ### 2. Input Audit
      
      List known, missing, conflicting, stale, out_of_scope, and assumptions with source, recency, and evidence quality.
      
      ### 3. quality gate Analysis and Priorities
      
      Describe scenarios, triggers, expected behavior, impact, priority, and evidence gaps for entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate.
      
      ### QGD-## Finding Contract
      
      Each finding must include:
      
      - object/rule
      - source
      - trigger or applicability
      - expected concern/rationale
      - evidence state
      - impact/priority
      - owner role
      - close condition
      - validation method
      
      ### 4. Candidate Validation and Residual Risk
      
      Separate candidate recommendations from actual execution and state the smallest validation action, stop/escalation conditions, residual risk, and open questions.
      
      ### 5. Human Decisions
      
      List only items requiring Human confirmation, risk acceptance, exception authorization, rollback, or release judgment.
      
      The output must keep these sections separate: facts, evidence-backed inferences, candidate recommendations, Human decisions.
      
      ## Quality Bar
      
      - Tailor the content to quality gate; do not merely rename a generic template.
      - Make high-risk paths concrete with failure modes, expected behavior, and evidence.
      - Never infer numbers, root causes, or system behavior without support.
      - Static analysis, plans, or dry runs are not proof of real execution, all tests passing, or release approval.
      - Let an executor act without guessing and a reviewer trace the boundary between facts, inferences, recommendations, and Human decisions.
      
  • SKILL.md 4.1 KB
    ---
    name: quality-gate-design
    description: Use this skill when you need evidence-bounded entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; triggers include 质量门禁 and quality gate.
    ---
    
    # Quality Gate Design
    
    ## When to Use
    
    - Use this skill when you need evidence-bounded analysis, design, or validation preparation for entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate.
    - Use it to review a plan, result, or metric and turn the review into executable improvements.
    - Use it when input is incomplete but a bounded first pass with assumptions, gaps, and human-decision boundaries is still useful.
    
    ## Output Format Options
    
    - Default to Markdown organized by domain risk, evidence state, priority, and boundary.
    - When the user requests tables, CSV, JSON, or ticket fields, preserve the same finding fields, evidence, and decision boundaries.
    - Before machine consumption, confirm the schema, enums, required fields, and evidence sources.
    
    ## How to Use
    
    1. Read and follow `prompts/quality-gate-design.md`, including its input audit, domain coverage, and output order.
    2. Extract scope, environment, version, time window, constraints, success criteria, and available evidence, with attention to gate objective, entry criteria, evidence source, owner role, exception and rollback.
    3. Separate confirmed facts, evidence-backed inferences, candidate recommendations, and Human decisions before ranking by risk and evidence strength.
    4. Turn high-risk items into preconditions, steps, expected behavior or decision criteria, required evidence, and a validation method.
    5. When input is incomplete, deliver a bounded first pass, state unsupported conclusions, and never present static material as execution evidence.
    
    ## Reference Files
    
    - Always read `prompts/quality-gate-design.md`; it is the complete execution specification for this skill.
    - For evaluation, read `evals/eval.yaml` and the matching cases under `evals/cases/`.
    - Load `references/`, `examples/`, `scripts/`, or `output-formats.md` only when those directories exist and the task needs them.
    
    ## Core Constraints
    
    - Keep the analysis focused on entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; do not replace business owners or Human risk acceptance, exception approval, or release decisions.
    - Never invent system behavior, fields, metrics, thresholds, data, root causes, execution records, or pass claims.
    - Static design, plans, file presence, or a dry run retain their evidence state and cannot become proof of real execution.
    - When evidence is insufficient, use pending confirmation, blocked, unassessed, or NOT_SCORED and give the smallest validation method.
    - For production, privacy, or security work, use least privilege, masked data, mocks, dry runs, or isolation.
    
    ## Delivery Checklist
    
    - [ ] Covered gate objective, entry criteria, evidence source, owner role, exception and rollback, with source, evidence state, and validation method for each.
    - [ ] Separated facts, inferences, candidate recommendations, gaps, and Human decisions.
    - [ ] Gave high-risk items P0/P1/P2/P3 or an equivalent priority, owner role, and close condition.
    - [ ] Did not turn plans, static checks, or dry runs into test execution, all-passed, or release-approved claims.
    - [ ] Stated residual risk, stop/escalation conditions, and next actions.
    
    ## Common Pitfalls
    
    - Listing checks without triggers, expected concerns, owner roles, close conditions, and evidence.
    - Treating adjacent metrics or tool names as a complete quality gate judgment.
    - Using unexplained numbers for false precision or writing correlation as causation.
    - Refusing incomplete input, or pretending that incomplete evidence is conclusive.
    
    ## Best Practices
    
    - Start with paths most likely to cause business loss, quality regression, or decision blockage.
    - Use the smallest verifiable experiment to reduce uncertainty and record conditions, versions, sources, and evidence.
    - Make the Skill independently installable, executable, and reviewable by another engineer.
    

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