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 agentmods add commands/vignesh2027/ai-agent-skills/testgit clone --depth 1 https://github.com/vignesh2027/AI-AGENT-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/commands/vignesh2027/ai-agent-skills/test)<a href="https://agentmods.dev/commands/vignesh2027/ai-agent-skills/test"><img src="https://agentmods.dev/badge/commands/vignesh2027/ai-agent-skills/test.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00148 |
| Opus 5 | $0.00000 | $0.00074 |
| Sonnet 5 | $0.00000 | $0.00030 |
| Haiku 4.5 | $0.00000 | $0.00015 |
Grade A, and why
test 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 6d 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.
What it actually says
Load skills/test-driven-development/SKILL.md and agents/test-engineer.md.
Write or review tests for the code described. Ensure:
- Happy path — Core behavior tested
- Error paths — Every error condition tested
- Edge cases — Empty, null, boundary values, concurrent access
- Test names — Describe expected behavior, not implementation
- Independence — Each test runs in isolation, order doesn't matter
- Speed — Tests must run in under 5 minutes for the local suite
For each missing test: describe what behavior it should cover and why it matters. For each poor test: explain what's wrong and provide an improved version.
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.
- 6d ago First seen · 14 lines · 0 tokens per session scan A aedae2bd1e00
test is a command published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 148 tokens. 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 2026-08-31.
Other commands, from other repositories
cpp-test
Enforce TDD workflow for C++. Write GoogleTest tests first, then implement. Verify coverage with gcov/lcov.
go-test
Go TDD workflow with table-driven tests.
api-aqa-flow
Workflow for backend API test automation: TMS / Issue Tracker test cases → automated API tests, HITL-gated.
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first.
feature-implement-execute
Phase 4 of develop: Execute the implementation plan with per-task TDD, quality gates, and completion verification.
usage-add
PitWay: Accumulate measured planning or qa token usage onto a milestone.