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 | $0.04001 |
| Opus 5 | $0.00066 | $0.02001 |
| Sonnet 5 | $0.00026 | $0.00800 |
| Haiku 4.5 | $0.00013 | $0.00400 |
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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 255 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, use it as the foundation and skip questions already answered there.
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.
- 9d 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 (114 stars, last pushed 3mo ago), licensed MIT. It adds 132 tokens to every session and 4,001 once invoked, about $0.0007 per session on Opus 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.
Other skills, from other repositories
Database Migration Test Generator
Generate tests for database migration safety covering schema changes, data integrity preservation, rollback verification, and zero-downtime migration validation.
Elasticsearch Testing Patterns
Elasticsearch testing including index management, query validation, mapping verification, bulk operation testing, and search relevance scoring.
pytest-databases
Auto-activate for pytestdatabases, Docker DB fixtures, PostgreSQL/pgvector/ParadeDB, MySQL/MariaDB, Oracle/SQL Server, CockroachDB/YugabyteDB, MongoDB, Redis/Valkey, Elasticsearch, BigQuery/Spanner, Azurite, MinIO, or RustFS tests. Not for mocked databases.
End-to-End Database Testing
End-to-end database testing with test containers, data seeding, cleanup strategies, transaction isolation, and production data anonymization.
Data Integrity Testing
Verifying data integrity constraints, referential integrity, data type validation, and consistency checks across database operations.
Database Migration Testing
Testing database migration scripts for correctness, rollback safety, data integrity, and zero-downtime migration patterns.