QA Plan

Port provenance: adapted from the pinned upstream source at 984023ddac0d5e27624f2baacde6105e45de375f under MIT; see the repository parity ledger for the exact path and blob.

QA Plan

This skill generates a structured QA plan for a sprint, feature, or individual story. It reads all in-scope story files and their referenced GDDs, classifies each story by test type, and produces a plan that tells developers exactly what to automate, what to verify manually, what the smoke test scope is, and when to bring in a playtester.

Run this before a sprint begins so the team knows upfront what testing work is required. A test plan written after implementation is a post-mortem, not a plan.

Output: production/qa/qa-plan-[sprint-slug]-[date].md

Phase 1: Parse Scope

Argument: the invocation arguments (blank = ask user via the available user-input mechanism)

Determine scope from the argument:

• sprint — read the most recent file in production/sprints/, extract every story file path referenced. If production/sprint-status.yaml exists, use it as the primary story list and fall back to the sprint plan for story metadata.
• feature: [system-name] — glob production/epics/*/story-*.md, filter to stories whose file path or title contains the system name. Also check the epic index file (EPIC.md) in that system's directory.
• story: [path] — validate that the path exists and load that single file.
• No argument — use the available user-input mechanism:
  • "What is the scope for this QA plan?"
  • Options: "Current sprint", "Specific feature (enter system name)", "Specific story (enter path)", "Full epic"

After resolving scope, report: "Building QA plan for [N] stories in [scope]."

If a story file path is referenced but the file does not exist, note it as MISSING and continue with the remaining stories. Do not fail the entire plan for one missing file.

Phase 2: Load Inputs

For each in-scope story file, read the full file and extract:

• Story title and story ID (from filename or header)
• Story Type field (if present in the file header — e.g., Type: Logic)
• Acceptance criteria — the complete numbered/bulleted list
• Implementation files — listed under "Files to Create / Modify" or similar
• Engine notes — any engine API warnings or version-specific notes
• GDD reference — the GDD path(s) cited
• ADR reference — the ADR(s) cited
• Estimate — hours or story points if present
• Dependencies — other stories this one depends on

After reading stories, load supporting context once (not per story):

• design/gdd/systems-index.md — to understand system priorities and which GDDs are approved
• For each unique GDD referenced across all stories: read the Acceptance Criteria, Formulas, and Edge Cases sections. Do not load the full GDD text. These three sections contain the testable requirements, the math to verify, and the boundary conditions that tests must cover. If an Edge Cases section is absent from the GDD, note it per GDD: "No Edge Cases section found — edge case coverage will be inferred from acceptance criteria only."
• docs/architecture/control-manifest.md — scan for forbidden patterns that automated tests should guard against (if the file exists)

If no GDD is referenced in a story, note it as a gap but do not block the plan. The story will be classified using acceptance criteria alone.

Phase 3: Classify Each Story

For each story, assign a Story Type:

• If the story already has a Type: field in its header: accept it as-is. Do NOT re-classify or validate against the criteria below — the Type was set by lead-programmer at story creation and is authoritative. Record it as-is.
• If the Type: field is missing: infer the type from the acceptance criteria using the table below, and note in the report that the type was inferred (not declared). Flag this as a gap — the story should have its Type declared explicitly before implementation begins.

Mixed stories (e.g., a story that adds both a formula and a UI display): assign the primary type based on which acceptance criteria carry the highest implementation risk, and note the secondary type. Mixed Logic+Integration or Visual+UI combinations are the most common.

After classifying all stories, produce a classification summary table in conversation before proceeding to Phase 4. This gives the user visibility into how tests will be allocated.

Phase 4: Generate Test Plan

Assemble the full QA plan document. Use this structure:

# QA Plan: [Sprint/Feature Name]
**Date**: [date]
**Generated by**: $ai-game-studio:qa-plan
**Scope**: [N stories across [N systems]]
**Engine**: [engine name from .ai-game-studio/project.json, or "Not configured"]
**Sprint File**: [path to sprint plan if applicable]

---

## Test Summary

| Story | Type | Automated Test Required | Manual Verification Required |
|-------|------|------------------------|------------------------------|
| [story title] | Logic | Unit test — `tests/unit/[system]/` | None |
| [story title] | Integration | Integration test — `tests/integration/[system]/` | Smoke check |
| [story title] | Visual/Feel | None (not automatable) | Screenshot + lead sign-off |
| [story title] | UI | Interaction walkthrough | Manual step-through |
| [story title] | Config/Data | Data validation test | Spot-check in-game values |

---

## Automated Tests Required

### [Story Title] — [Type]
**Test file path**: `tests/[unit|integration]/[system]/[story-slug]_test.[ext]`
**What to test**:
- [Specific formula or rule from the GDD Formulas section]
- [Each named state transition or decision branch]
- [Each side effect that should or should not occur]

**Edge cases to cover**:
- Zero/minimum input values (e.g., 0 damage, empty inventory)
- Maximum/boundary input values (e.g., max level, stat cap)
- Invalid or null input (e.g., missing target, dead entity)
- [Any edge case explicitly called out in the GDD Edge Cases section]

**Estimated test count**: ~[N] unit tests

[If no GDD formula reference was found for this story, note:]
*No formula found in referenced GDD — test cases must be derived from acceptance
criteria directly. Review the GDD Formulas section before writing tests.*

---

## Manual QA Checklist

### [Story Title] — [Type]
**Verification method**: [Screenshot + designer sign-off | Playtest session |
Manual step-through | Comparison against reference footage]
**Who must sign off**: [designer / lead-programmer / qa-lead / art-lead]
**Evidence to capture**: [screenshot of X | video clip of Y | written playtest
notes | side-by-side comparison]

Checklist:
- [ ] [Specific observable condition — concrete and falsifiable]
- [ ] [Another condition]
- [ ] [Every acceptance criterion translated into a manual check item]

*If any criterion uses subjective language ("feels", "looks", "seems"), it must
be supplemented with a specific benchmark or a playtest protocol note.*

---

## Smoke Test Scope

Critical paths to verify before any QA hand-off for this sprint:

1. Game launches to main menu without crash
2. New game / new session can be started
3. [Primary mechanic introduced or changed this sprint]
4. [Any system with a regression risk from this sprint's changes]
5. Save / load cycle completes without data loss (if save system exists)
6. Performance is within budget on target hardware (no new frame spikes)

*Smoke tests are verified by the developer via `$ai-game-studio:smoke-check`. Reference this
list when running that skill.*

---

## Playtest Requirements

| Story | Playtest Goal | Min Sessions | Target Player Type |
|-------|--------------|--------------|-------------------|
| [story] | [What question must the session answer?] | [N] | [new player / experienced] |

**Sign-off requirement**: Playtest notes must be written to
`production/session-logs/playtest-[sprint]-[story-slug].md` and reviewed by
the [designer / qa-lead] before the story can be marked COMPLETE.

If no stories require playtest validation: *No playtest sessions required for
this sprint.*

---

## Definition of Done — This Sprint

A story is DONE when ALL of the following are true:

- [ ] All acceptance criteria verified — via automated test result OR documented
      manual evidence (screenshot, video, or playtest notes with sign-off)
- [ ] Test file exists at the specified path for all Logic and Integration stories
- [ ] Manual evidence document exists for all Visual/Feel and UI stories
- [ ] Smoke check passes (run `$ai-game-studio:smoke-check sprint` before QA hand-off)
- [ ] No regressions introduced
- [ ] Code reviewed (via `$ai-game-studio:code-review` or documented peer review)
- [ ] Story file updated to `Status: Complete` (via `$ai-game-studio:story-done`)

When generating content, use the actual story titles, GDD formula text, and acceptance criteria extracted in Phase 2. Do not use placeholder text — every test entry should reflect the real requirements of these specific stories.

Phase 5: Write Output

Show the complete plan in conversation (or a summary if the plan is very long), then ask two questions together using the available user-input mechanism:

question: "Ready to write the QA plan. Choose output options:"
multiSelect: true
options:
  - "Write QA plan to production/qa/qa-plan-[sprint-slug]-[date].md"
  - "Also back-fill test case specs into each story file's ## QA Test Cases section (Recommended — enables $ai-game-studio:dev-story and $ai-game-studio:code-review traceability)"

If "Write QA plan" is selected: write the plan file exactly as generated — do not truncate.

If "Also back-fill story files" is selected: for each Logic and Integration story in scope, edit the story file at its path. Find the ## QA Test Cases section and replace its content with the test case specs generated in Phase 4 for that story. If a story has no ## QA Test Cases section, append it before ## Test Evidence. For Visual/Feel and UI stories, write the manual verification steps instead of test specs.

After writing:

"QA plan written to production/qa/qa-plan-[sprint-slug]-[date].md.

Next steps:

• Share this plan with the team before sprint implementation begins
• Once all sprint stories are implemented, run $ai-game-studio:smoke-check sprint to gate QA hand-off — not yet, only after implementation is complete
• For Logic/Integration stories, create the test files at the listed paths before marking stories done — $ai-game-studio:story-done checks for them"

Silently append to production/session-state/active.md (create the file if it does not exist):

<!-- QA-PLAN: [date] | System: [system/sprint identifier] | Plan written: production/qa/qa-plan-[identifier]-[date].md -->

Collaborative Protocol

• Never write the plan without asking — Phase 5 requires explicit approval.
• Classify conservatively: when a story is ambiguous between Logic and Integration, classify it as Integration — it requires both unit and integration tests.
• Do not invent test cases beyond what acceptance criteria and GDD formulas support. If a formula is absent from the GDD, flag it rather than guessing.
• Playtest requirements are advisory: the user decides whether a playtest is warranted for borderline Visual/Feel stories. Flag the case; do not mandate.
• Use the available user-input mechanism for scope selection when no argument is provided. Keep all other phases non-interactive — present findings, then ask once to approve the write.

Codex portability

Use the search, file-editing, shell, user-input, and subagent capabilities available in the active Codex surface. Use PowerShell syntax on Windows and POSIX syntax on macOS/Linux; do not require a Unix compatibility layer on Windows. Inherit the active model and permission mode, and do not weaken approval or sandbox boundaries.