Agent skill

Sprint QA Plan

by Donchitos in Donchitos/Claude-Code-Game-Studios

Produces a sprint QA plan that classifies stories as logic, integration, visual or UI and sets automated tests, manual checks and smoke scope for each.

MITAuto-check passedTesting & QA

Install Sprint QA Plan

skills CLI
$ npx skills add Donchitos/Claude-Code-Game-Studios --skill qa-plan -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Donchitos/Claude-Code-Game-Studios qa-plan --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-Studios.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/qa-plan .claude/skills/qa-plan && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qa-plan
GitHub stars
26k
Token cost
~4.4k tokens
SKILL.md length
1,666 words
Files
1
Skills in repo
73
Repo updated
First seen
Licence
MIT

At a glance

Produces a sprint QA plan that classifies stories as logic, integration, visual or UI and sets automated tests, manual checks and smoke scope for each.

  • Works in 5 steps: Parse Scope → Load Inputs → Classify Each Story → …
  • Planning the testing work for a sprint before implementation begins
  • SKILL.md covers Phase 1: Parse Scope, Phase 2: Load Inputs, Phase 3: Classify Each Story and Phase 4: Generate Test Plan, plus 2 more sections
  • Calls bash

What it does

The skill reads the in-scope story files and the design documents they reference, classifies each story by test type, and writes a plan saying what to automate, what to verify manually, what the smoke test covers and when to involve a playtester. Scope can be a sprint (the latest sprint file, or `production/sprint-status.yaml` when present), a feature named by system, or a single story path. With no argument it asks. The plan is saved as a dated file under `production/qa/`.

Run it before the sprint starts, because a test plan written after implementation is only a post-mortem. The `qa.level` setting scales the output: minimal gives a smoke plan only, standard gives a full plan per story type, and full adds per-system coverage targets. No level drops the visual and UI screenshot rows, since tests can be waived but how the game looks cannot.

When your agent uses it

  • Planning the testing work for a sprint before implementation begins
  • Deciding which stories need automated tests and which need manual checks
  • Defining smoke test scope and when to bring in a playtester

Example prompts

  • “Create a QA plan for the current sprint.”
  • “Write a QA plan for the feature combat-system using its story files.”
  • “Plan the testing for the story in production/epics/ui/story-health-bar.md.”

Requirements

  • Story files under `production/` and the GDDs they reference
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Write, Edit, AskUserQuestion, Bash(bash "*/.claude/skills/qa-plan/../../hooks/yaml-helper.sh" resolve_config *)

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Parse Scope
  2. Load Inputs
  3. Classify Each Story
  4. Generate Test Plan
  5. Write Output

What it can do on your machine

Read from SKILL.md and the folder at commit b21fa0f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Write
    • Edit
    • AskUserQuestion
    • Bash(bash "*/.claude/skills/qa-plan/../../hooks/yaml-helper.sh" resolve_config *)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sprint QA Plan loads about 4.4k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 1,666 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Donchitos/Claude-Code-Game-Studios at commit b21fa0f, republished under its MIT licence (© Donchitos). 1,666 words, ~4,415 tokens.

Download SKILL.mdSave it as .claude/skills/qa-plan/SKILL.md (or your agent's skills folder).
name
qa-plan
description
QA test plan for a sprint — classifies stories by Logic/Integration/Visual/UI, covers automated tests, manual cases, smoke scope.
allowed-tools
Read, Glob, Grep, Write, Edit, AskUserQuestion, Bash(bash "*/.claude/skills/qa-plan/../../hooks/yaml-helper.sh" resolve_config *)
argument-hint
[sprint | feature: system-name | story: path]
user-invocable
true
model
sonnet

!bash "${CLAUDE_SKILL_DIR}/../../hooks/yaml-helper.sh" resolve_config --keys automation,workflow,qa.level,system_overrides

Resolved above — use as-is. No block → defaults in .claude/docs/config-resolution.md.

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


Every AskUserQuestion call follows .claude/docs/automation-modes.md (collaborative asks always · guided major-only · autonomous logs and proceeds; automation_always_ask categories always prompt).

Workflow tier: resolve per the GDD's system as each is read (per .claude/docs/workflow-modes.md): workflow_overrides.system_overrides.<system> if the block lists one, else the project value. It sets how many GDD sections the test plan is mined from — see Phase 2.

qa.level: at minimal, produce only a minimal smoke plan — drop the automated-test-required rows and the test-file DoD; at standard, a full plan per story type; at full, also add per-system coverage targets. Distinct axis from workflow (which sets how many GDD sections are mined). No level drops the Visual/Feel and UI screenshot rows — tests are waived at minimal, the look is not (.claude/docs/coding-standards.md).

Phase 1: Parse Scope

Argument: $ARGUMENTS (blank = ask user via AskUserQuestion)

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 AskUserQuestion:
    • "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.

If the resolved scope contains ZERO stories, stop — do not build a plan. Report NOT ASSESSED — no stories in scope, naming which scope was searched and which path was empty, and route:

  • no file in production/sprints/ → "No sprint plan found. Run /sprint-plan new." At workflow: minimal there are no sprints by design — route instead to /qa-plan feature: [epic-slug] or /qa-plan story: [path].
  • a sprint plan exists but references no stories → "Sprint plan [path] lists no stories. Run /create-stories [epic-slug]."
  • feature:/story: scope matched nothing → name the glob that came back empty.

The N=0 guard is mandatory. Without it an empty scope reports "Building QA plan for 0 stories" and continues into Phase 4, producing a plan document with empty tables — and a QA plan for zero stories looks exactly like a completed QA plan. This skill gates the hand-off to manual QA, so a false-clean here sends a build to QA on the strength of a plan that tested nothing.

Note the shape, because this skill already had the harder half of the rule. Phase 2 states "Never treat an absent section as an absent story" — the sophisticated inner case, correctly handled. The outer boundary, no stories at all, had nothing. The same shape appears in /story-readiness, where NOT ASSESSED existed for per-story failures and the empty scope could not reach it.

The rule at the top of this block still stands: one missing file among several is MISSING-and-continue. This is the different case where there is no several.


Phase 2: Load Inputs

Establish the denominator first — glob the in-scope story files and count N — then collect the fields below with targeted section greps, not a full read of each story. A QA plan needs each story's type and acceptance criteria; it does not need its implementation notes, out-of-scope boundaries or ADR rationale, and reading N stories whole to reach two sections is where this phase's cost lives:

Grep pattern="^## Acceptance Criteria" glob="production/epics/**/story-*.md" output_mode="content" -A 15
Grep pattern="^> \*\*(Type|Status|Estimate)\*\*" glob="production/epics/**/story-*.md" output_mode="content"
Grep pattern="^## (Context|Dependencies)" glob="production/epics/**/story-*.md" output_mode="content" -A 8

(Scope the globs to the sprint plan's story paths in sprint mode.) From those:

  • Story title and story ID — from the file name and path; no read at all
  • Story Type field — from the header grep (e.g., Type: Logic)
  • Acceptance criteria — the complete numbered/bulleted list, from the first grep
  • GDD / ADR reference and Dependencies — from the ## Context grep
  • Estimate — from the header grep if present
  • Implementation files and Engine notes — only needed for stories whose test plan actually turns on them; full-read those individual stories

Never treat an absent section as an absent story. If a story matched no ## Acceptance Criteria, full-read that one and say so — a story with no testable criteria is a QA finding in its own right, not a story to skip.

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: mine test material per that system's workflow tier (resolved above) — at full, mine all 8 sections; at standard, mine the test-relevant subset of the required sections (Acceptance Criteria and Edge Cases always, plus Formulas for any system that defines numeric rules); at minimal, Acceptance Criteria only. Do not load the full GDD text. These sections contain the testable requirements, the math to verify, and the boundary conditions tests must cover. If an Edge Cases section is absent (or not expected at minimal), note 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.


Show full SKILL.md (669 more words)Show less

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.
Story TypeClassification Indicators
LogicAcceptance criteria reference calculations, formulas, numerical thresholds, state transitions, AI decisions, data validation, buff/debuff stacking, economy transactions, or any testable computation
IntegrationCriteria involve two or more systems interacting, signals or events propagating across system boundaries, save/load round-trips, network sync, or persistence
Visual/FeelCriteria reference animation behaviour, VFX, shader output, "feels responsive", perceived timing, screen shake, particle effects, audio sync, or visual feedback quality
UICriteria reference menus, HUD elements, buttons, screens, dialogue boxes, inventory panels, tooltips, or any player-facing interface element
Config/DataChanges are limited to balance tuning values, data files, or configuration — no new code logic is involved

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:

markdown
# QA Plan: [Sprint/Feature Name]
**Date**: [date]
**Generated by**: /qa-plan
**Scope**: [N stories across [N systems]]
**Engine**: [engine name — `engine.name` from project.yaml if present and non-empty, else the Engine field from .claude/docs/technical-preferences.md, else "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 | None (verified by its screenshots) | Retained screenshot of each screen touched |
| [story title] | Config/Data | Data validation test | Spot-check in-game values |

---

## Automated Tests Required

*(At `qa.level: minimal`, omit this entire section and blank the Test Summary's
"Automated Test Required" column — automated tests are not required there; list
manual/smoke verification only.)*

### [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-director]
**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 `/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 (at `qa.level: minimal`, drop
the test-file and smoke rows below — tests are waived there; the screenshot and
sign-off rows stay at every level, because the look is not):

- [ ] 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 *(qa.level standard/full)*
- [ ] Retained screenshot of each screen touched, in `production/qa/evidence/`, for all Visual/Feel and UI stories *(every qa.level)*
- [ ] Signed-off evidence doc at `production/qa/evidence/[story-slug]-evidence.md` for all Visual/Feel stories *(every qa.level)*
- [ ] Smoke check passes (run `/smoke-check sprint` before QA hand-off) *(qa.level standard/full)*
- [ ] No regressions introduced
- [ ] Code reviewed (via `/code-review` or documented peer review)
- [ ] Story file updated to `Status: Complete` (via `/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 AskUserQuestion:

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 /dev-story and /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 /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 — /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 -->

Close with the verdict: COMPLETE — QA plan written (or COMPLETE — QA plan shown, not written, if the write was declined). The only other outcome is the NOT ASSESSED — no stories in scope path in Phase 1.


Collaborative Protocol

Applies in collaborative mode (the default). For guided and autonomous modes, see .claude/docs/automation-modes.md — the rules below describe what collaborative mode requires, not universal behavior.

  • 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 AskUserQuestion for scope selection when no argument is provided. Keep all other phases non-interactive — present findings, then ask once to approve the write.

© Donchitos, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/qa-plan of Donchitos/Claude-Code-Game-Studios.

Open the folder on GitHubat commit b21fa0f

Compare with similar skills

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Questions about Sprint QA Plan

What does Sprint QA Plan do?

Produces a sprint QA plan that classifies stories as logic, integration, visual or UI and sets automated tests, manual checks and smoke scope for each. The skill reads the in-scope story files and the design documents they reference, classifies each story by test type, and writes a plan saying what to automate, what to verify manually, what the smoke test covers and when to involve a playtester.yaml` when present), a feature named by system, or a single story path.

When should I use Sprint QA Plan?

Sprint QA Plan fits situations like: planning the testing work for a sprint before implementation begins; deciding which stories need automated tests and which need manual checks; defining smoke test scope and when to bring in a playtester.

How do I install Sprint QA Plan in Claude Code?

Run `npx skills add Donchitos/Claude-Code-Game-Studios --skill qa-plan -a claude-code`. Or copy the skill folder (.claude/skills/qa-plan in Donchitos/Claude-Code-Game-Studios) into .claude/skills/qa-plan in your project. Claude Code loads it when a task matches its description.

How do I install Sprint QA Plan in Codex?

Run `npx skills add Donchitos/Claude-Code-Game-Studios --skill qa-plan -a codex`. Or copy the skill folder (.claude/skills/qa-plan in Donchitos/Claude-Code-Game-Studios) into .agents/skills/qa-plan in your project. Codex loads it when a task matches its description.

Can I use Sprint QA Plan in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Donchitos/Claude-Code-Game-Studios --skill qa-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qa-plan, .gemini/skills/qa-plan, .github/skills/qa-plan and .opencode/skills/qa-plan in your project.

What does Sprint QA Plan need to run?

Going by SKILL.md and its folder, Sprint QA Plan needs the command-line tools its instructions call (bash). Our summary lists: Story files under `production/` and the GDDs they reference. Its frontmatter pre-approves these tools: Read, Glob, Grep, Write, Edit, AskUserQuestion, Bash(bash "*/.claude/skills/qa-plan/../../hooks/yaml-helper.sh" resolve_config *).

Does Sprint QA Plan access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Sprint QA Plan safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Sprint QA Plan use?

Sprint QA Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sprint QA Plan use?

About 4.4k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Sprint QA Plan?

Skills that share tags, products or a category with Sprint QA Plan: Senior QA (nicepkg/auto-company, 192 stars), Robotics Testing (arpitg1304/robotics-agent-skills, 368 stars), QA Manual Istqb (fugazi/test-automation-skills-agents, 247 stars) and Next QA Idea (breaking-brake/cc-wf-studio, 5.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sprint QA Plan?

Donchitos (a GitHub user) maintains it in Donchitos/Claude-Code-Game-Studios, which has 25,871 GitHub stars. The repository holds 73 skills in this directory. The repository was last updated on September 29, 2026.

Source: Donchitos/Claude-Code-Game-Studios on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.