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 petrkindlmann/qa-skills --skill test-data-managementgit clone --depth 1 https://github.com/petrkindlmann/qa-skillsWrote 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/petrkindlmann/qa-skills/test-data-management)<a href="https://agentmods.dev/skills/petrkindlmann/qa-skills/test-data-management"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/test-data-management/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/petrkindlmann/qa-skills/test-data-management"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/test-data-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00132 | $0.04421 |
| Opus 5.5 | $0.00053 | $0.01768 |
| Sonnet 5.5 | $0.00026 | $0.00884 |
| Haiku 4.5 | $0.00013 | $0.00442 |
Grade A, and why
test-data-management 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quick Route
| Situation | Go to |
|---|---|
| Need fresh entity data with per-test overrides | Factory Patterns → references/factories.md |
| Mocking an API response or golden file | Fixture Strategies → references/factories.md |
| Copying production data anywhere non-prod | Data Anonymization |
| Populating a test DB / reference data idempotently | Database Seeding → references/seeding-and-synthetic.md |
| Cleaning up after tests / parallel isolation | Cleanup Strategies → references/seeding-and-synthetic.md |
| Generating edge cases and boundary values | Synthetic Data → references/seeding-and-synthetic.md |
Discovery Questions
Before designing a test data strategy, understand the current state. Check .agents/qa-project-context.md first -- if it exists and is filled in, use it as the foundation and skip questions already answered there; an unfilled template answers nothing, so treat it as absent.
Current Data Practices
- How is test data created today? (manually, scripts, copy of production, none)
- Do tests share data or does each test create its own?
- How is test data cleaned up? (truncate, rollback, manual, never)
- Are there seed scripts? Are they idempotent?
Privacy and Compliance
- Does the product handle PII? (names, emails, addresses, phone numbers, SSNs)
- Are there GDPR, HIPAA, PCI-DSS, or other data protection requirements?
- Is production data ever used in test environments?
Scale and Complexity
- How large are the test datasets? (dozens of records, thousands, millions)
- How complex are the data relationships? (simple CRUD, deep nested hierarchies, polymorphic)
- Are there cross-service data dependencies? (microservices sharing data)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday Changed · +1 lines f279e04efafe
- 1mo ago First seen · 255 lines · 132 tokens per session scan A e8bd7ce43c8b
test-data-management is a skill published in the GitHub repository petrkindlmann/qa-skills (207 stars, last pushed 2d ago), licensed MIT. It adds 132 tokens to every session and 4,421 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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