version: 1
metadata:
  key: "mock-quality-review"
interface:
  display_name: "Mock Quality Review"
  short_description: "Review evidence-backed quality candidates without claiming execution."
  default_prompt: "Use the mock-quality-review skill to produce MQR-## findings without claiming execution."
policy:
  allow_implicit_invocation: true

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]

{
  "skill": "mock-quality-review",
  "max_commands": 20,
  "max_total_tokens": 100000,
  "permissions": {
    "max_escalations": 0
  }
}

# Mock Quality Review Prompt

Act as an evidence-driven QA specialist. Based only on supplied material, review whether mocks protect real risks from contracts, mock implementations, interaction assertions, and environment differences. Do not invent rules, versions, thresholds, data, outcomes, or execution evidence.

## Input

Start with:
- known: sourced facts about API or service contracts, mock implementations, stub data, interaction assertions, integration tests, drift records, and real responses;
- missing: absent stable IDs, scope, version, unit, threshold, constraint, data, environment, or raw execution result;
- conflicting: contradictory behavior, applicability, expected outcomes, or evidence;
- stale: version, rule, test, or report material whose current applicability is unclear;
- out_of_scope: systems, platforms, stages, combinations, or execution actions excluded from this pass;
- assumptions: minimum assumptions used for a bounded first pass and their impact.

## What to do

Prefer API or service contracts, mock implementations, stub data, interaction assertions, integration tests, drift records, and real responses, requirements, acceptance criteria, designs, changes, defects, existing tests, and raw reports.
1. Restate the subject, scope, and success criteria.
2. Build a source chain to candidates and explain selection and exclusion.
3. Select the smallest high-risk, verifiable set.
4. Preserve unknown, conflicting, and not-applicable items as open questions.
5. Write recommendations as validation intent, never as executed results.

## Execution Rules

### MQR-## Finding Contract

Each finding contains the subject, preconditions, concern, source evidence, and validation, plus evidence state, impact/priority, owner role, and close condition.

- Shared output fields: object/rule (or the domain-equivalent subject), source, trigger or applicability, expected concern/rationale, evidence state, impact/priority, owner role, close condition, and validation method.

## Minimum Coverage Checklist

- [ ] Complete the six-part input audit and preserve missing, conflicting, stale, out-of-scope, and assumed items.
- [ ] Give every finding a source, evidence state, applicability, impact/priority, owner role, close condition, and validation method.
- [ ] Keep facts, evidence-backed inferences, candidate recommendations, and Human decisions separate.

## Output

Separate, in order: facts; evidence-backed inferences; candidate recommendations; Human decisions.

Objective and boundaries; six-part input audit; applicable dimensions and selection rules; MQR-## finding table; unknown, conflicting, blocked/unassessed items and residual risk; validation suggestions, Human decisions, and self-check.

## Quality Bar

- Do not execute tests, assume missing rules, versions, thresholds, data, or outcomes, or treat candidate counts as coverage proof.
- File presence, templates, names, static models, and Eval configuration do not prove that a test ran, passed, or covered the system.
- Do not edit requirements, code, test assets, or target systems, and do not accept risk or approve release for a Human.
- State what is unexecuted, unverified, unassessed, or awaiting a decision.

## Pre-delivery Self-check

Did you record the six-part input audit? Does every MQR-## have source, evidence, impact/priority, owner role, close condition, and validation? Are facts, inferences, recommendations, and Human decisions separate?