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.
git clone --depth 1 https://github.com/fitlab-ai/agent-infraWrote 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/fitlab-ai/agent-infra/test.en)<a href="https://agentmods.dev/commands/fitlab-ai/agent-infra/test.en"><img src="https://agentmods.dev/badge/commands/fitlab-ai/agent-infra/test.en.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 | $0.00006 | $0.00038 |
| Opus 5 | $0.00003 | $0.00019 |
| Sonnet 5 | $0.00001 | $0.00008 |
| Haiku 4.5 | $0.00001 | $0.00004 |
Grade A, and why
test.en 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 5d 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
Read and execute the test skill from .agents/skills/test/SKILL.md.
Follow all steps defined in the skill exactly.
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.
- 5d ago First seen · 8 lines · 6 tokens per session scan A b0f3d40afd98
test.en is a command published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed yesterday), licensed MIT. It adds 6 tokens to every session and 38 once invoked, about $0.0000 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 2026-09-03.
Other commands, from other repositories
feature-implement-execute
Phase 4 of develop: Execute the implementation plan with per-task TDD, quality gates, and completion verification.
pr-dance
Loop a PR through CI and bot review until merge-ready. Use when user says '/pr-dance', 'do the PR dance', or finishing-a-development-branch dispatches option 3.
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
fix-tests-execute
Phase 2 of fixing-tests: Fix Execution - investigate, classify, fix, verify, and commit each work item.
test-bar
Generate a floating QA test overlay for the current branch's UI changes. Use when user says /test-bar, needs visual QA scenarios, or wants to test conditional rendering paths.
write-skill-test
RED-GREEN-REFACTOR implementation for writing-skills: Baseline testing, minimal skill writing, loophole closure, and full creation checklist.