### Test Evidence Review
Works with
name: test-evidence-review
description: "Quality review of test files and manual evidence documents. Goes beyond existence checks — evaluates assertion coverage, edge case handling, naming conventions, and evidence completeness
argument-hint: "[story-path | sprint | system-name]"
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontest-evidence-reviewExecute the skills CLI command in your project's root directory to begin installation:
Fetches test-evidence-review from Donchitos/Claude-Code-Game-Studios and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate test-evidence-review. Access via /test-evidence-review in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| name | test-evidence-review |
| description | "Quality review of test files and manual evidence documents. Goes beyond existence checks — evaluates assertion coverage, edge case handling, naming conventions, and evidence completeness. Produces ADEQUATE/INCOMPLETE/MISSING verdict per story. Run before QA sign-off or on demand." |
| argument-hint | "[story-path | sprint | system-name]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Write |
/smoke-check verifies that test files exist and pass. This skill
goes further — it reviews the quality of those tests and evidence documents.
A test file that exists and passes may still leave critical behaviour uncovered.
A manual evidence doc that exists may lack the sign-offs required for closure.
Output: Summary report (in conversation) + optional production/qa/evidence-review-[date].md
When to run:
/team-qa Phase 5)Modes:
/test-evidence-review [story-path] — review a single story's evidence/test-evidence-review sprint — review all stories in the current sprint/test-evidence-review [system-name] — review all stories in an epic/systemBased on the argument:
Single story: Read the story file directly. Extract: Story Type, Test Evidence section, story slug, system name.
Sprint: Read the most recently modified file in production/sprints/.
Extract the list of story file paths from the sprint plan. Read each story file.
System: Glob production/epics/[system-name]/story-*.md. Read each.
For each story, collect:
Type: field (Logic / Integration / Visual/Feel / UI / Config/Data)## Test Evidence section — the stated expected test file path or evidence docFor each story, find the evidence:
Logic stories: Glob tests/unit/[system]/[story-slug]_test.*
tests/unit/[system]/ for files
containing the story slugIntegration stories: Glob tests/integration/[system]/[story-slug]_test.*
production/session-logs/ for playtest records mentioning the storyVisual/Feel and UI stories: Glob production/qa/evidence/[story-slug]-evidence.*
Config/Data stories: Glob production/qa/smoke-*.md (any smoke check report)
Note what was found (path) or not found (gap) for each story.
For each test file found, read it and evaluate:
Count the number of distinct assertions (lines containing assert, expect, check, verify, or engine-specific assertion patterns). Low assertion count is a quality signal — a test that makes only 1 assertion per test function may not cover the range of expected behaviour.
Thresholds:
For each acceptance criterion in the story that contains a number, threshold, or "when X happens" conditional: check whether a test function name or test body references that specific case.
Heuristics:
Test function names should describe: the scenario + the expected result.
Pattern: test_[scenario]_[expected_outcome]
Flag functions named generically (test_1, test_run, testBasic) as
naming issues — they make failures harder to diagnose.
For Logic stories where the GDD has a Formulas section: check that the test file contains at least one test whose name or comment references the formula name or a formula value. A test that exercises a formula without mentioning it by name is harder to maintain when the formula changes.
For each evidence document found, read it and evaluate:
The evidence doc should reference each acceptance criterion from the story. Check: does the evidence doc contain each criterion (or a clear rephrasing)? Missing criteria mean a criterion was never verified.
Check for three sign-off lines (or equivalent fields):
If any are missing or blank: flag as INCOMPLETE — the story cannot be fully closed without all required sign-offs.
For Visual/Feel stories: check whether screenshot file paths are referenced in the evidence doc. If referenced, Glob for them to confirm they exist.
For UI stories: check whether a walkthrough sequence (step-by-step interaction log) is present.
Evidence doc should have a date. If the date is earlier than the story's last major change (heuristic: compare against sprint start date from the sprint plan), flag as POTENTIALLY STALE — the evidence may not cover the final implementation.
For each story, assign a verdict:
| Verdict | Meaning |
|---|---|
| ADEQUATE | Test/evidence exists, passes quality checks, all criteria covered |
| INCOMPLETE | Test/evidence exists but has quality gaps (thin assertions, missing sign-offs) |
| MISSING | No test or evidence found for a story type that requires it |
The overall sprint/system verdict is the worst story verdict present.
## Test Evidence Review
> **Date**: [date]
> **Scope**: [single story path | Sprint [N] | [system name]]
> **Stories reviewed**: [N]
> **Overall verdict**: ADEQUATE / INCOMPLETE / MISSING
---
### Story-by-Story Results
#### [Story Title] — [Type] — [ADEQUATE/INCOMPLETE/MISSING]
**Test/evidence path**: `[path]` (found) / (not found)
**Automated test quality** *(Logic/Integration only)*:
- Assertion coverage: [N per function on average] — [adequate / thin / none]
- Edge cases: [covered / partial / not found]
- Naming: [consistent / [N] generic names flagged]
- Formula traceability: [yes / no — formula names not referenced in tests]
**Manual evidence quality** *(Visual/Feel/UI only)*:
- Criterion linkage: [N/M criteria referenced]
- Sign-offs: [Developer ✓ | Designer ✗ | QA Lead ✗]
- Artefacts: [screenshots present / missing / N/A]
- Freshness: [dated [date] — current / potentially stale]
**Issues**:
- BLOCKING: [description] *(prevents story-done)*
- ADVISORY: [description] *(should fix before release)*
---
### Summary
| Story | Type | Verdict | Issues |
|-------|------|---------|--------|
| [title] | Logic | ADEQUATE | None |
| [title] | Integration | INCOMPLETE | Thin assertions (avg 1.2/function) |
| [title] | Visual/Feel | INCOMPLETE | QA lead sign-off missing |
| [title] | Logic | MISSING | No test file found |
**BLOCKING items** (must resolve before story can be closed): [N]
**ADVISORY items** (should address before release): [N]
Present the report in conversation.
Ask: "May I write this test evidence review to
production/qa/evidence-review-[date].md?"
This is optional — the report is useful standalone. Write only if the user wants a persistent record.
After the report:
/story-done can mark the
story Complete. Would you like to address any of them now?"/test-helpers [system] to see
scaffolded assertion patterns for common cases."[evidence-path] with them to complete sign-off."Verdict: COMPLETE — evidence review finished. Use CONCERNS if BLOCKING items were found.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Useful defaults in test-evidence-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
test-evidence-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for test-evidence-review matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend test-evidence-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
test-evidence-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
test-evidence-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added test-evidence-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
test-evidence-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: test-evidence-review is focused, and the summary matches what you get after install.
test-evidence-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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