Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add striderZA/OpenCodeGameStudios --skill team-qagit clone --depth 1 https://github.com/striderZA/OpenCodeGameStudiosWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/striderza/opencodegamestudios/team-qa)<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/team-qa"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/team-qa/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/team-qa"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/team-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.02391 |
| Opus 5.5 | $0.00029 | $0.00956 |
| Sonnet 5.5 | $0.00015 | $0.00478 |
| Haiku 4.5 | $0.00007 | $0.00239 |
Grade A, and why
team-qa scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
80% identical to team-qa — 255 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When this skill is invoked, orchestrate the QA team through a structured testing cycle.
Decision Points: At each phase transition, use question to present
the user with the subagent's proposals as selectable options. Write the agent's
full analysis in conversation, then capture the decision with concise labels.
The user must approve before moving to the next phase.
Team Composition
- qa-lead — QA strategy, test plan generation, story classification, sign-off report
- qa-tester — Test case writing, bug report writing, manual QA documentation
How to Delegate
Use the Task tool to spawn each team member as a subagent:
subagent_type: qa-lead— Strategy, planning, classification, sign-offsubagent_type: qa-tester— Test case writing and bug report writing
Always provide full context in each agent's prompt (story file paths, QA plan path, scope constraints). Launch independent qa-tester tasks in parallel where possible (e.g., multiple stories in Phase 5 can be scaffolded simultaneously).
Pipeline
Phase 1: Load Context
Before doing anything else, gather the full scope:
-
Detect the current sprint or feature scope from the argument:
- If argument is a sprint identifier (e.g.,
sprint-03): read all story files inproduction/sprints/[sprint]/ - If argument is
feature: [system-name]: glob story files tagged for that system - If no argument: read
production/session-state/active.mdandproduction/sprint-status.yaml(if present) to infer the active sprint
- If argument is a sprint identifier (e.g.,
-
Read
production/stage.txtto confirm the current project phase. -
Count stories found and report to the user:
"QA cycle starting for [sprint/feature]. Found [N] stories. Current stage: [stage]. Ready to begin QA strategy?"
Phase 2: QA Strategy (qa-lead)
Spawn qa-lead via Task to review all in-scope stories and produce a QA strategy.
Prompt the qa-lead to:
- Read each story file
- Classify each story by type: Logic / Integration / Visual/Feel / UI / Config/Data
- Identify which stories require automated test evidence vs. manual QA
- Flag any stories with missing acceptance criteria or missing test evidence that would block QA
- Estimate manual QA effort (number of test sessions needed)
- Check
tests/smoke/for smoke test scenarios; for each, assess whether it can be verified given the current build. Produce a smoke check verdict: PASS / PASS WITH WARNINGS [list] / FAIL [list of failures] - Produce a strategy summary table and smoke check result:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 223 lines · 73 tokens per session scan A 92a370ccfdce
team-qa is a skill published in the GitHub repository striderZA/OpenCodeGameStudios (99 stars, last pushed 13d ago), licensed MIT. It adds 73 tokens to every session and 2,391 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 80% identical to team-qa, differing in 255 lines, and is treated as a copy.
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team-combat
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team-polish
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procgen-design
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animation-state-patterns
Structure animation state, blending, events, and sync so authored motion remains reliable under gameplay pressure.
qa-test-matrix
Build a coverage matrix that shows what must be tested, on which configurations, and at what milestone confidence level.
godot-testing
Choose effective automated and manual test layers for Godot features without overcomplicating the project.