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/athola/claude-night-marketWrote 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/athola/claude-night-market/test-skill)<a href="https://agentmods.dev/commands/athola/claude-night-market/test-skill"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/test-skill/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/commands/athola/claude-night-market/test-skill"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/test-skill.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 | $0.00029 | $0.00257 |
| Opus 5 | $0.00015 | $0.00129 |
| Sonnet 5 | $0.00006 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
test-skill 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 10d 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
Test Skill
Runs skill validation via superpowers:test-driven-development while keeping the familiar /test-skill interface.
When To Use
Use this command when you need to:
- Testing a skill through RED/GREEN/REFACTOR phases
- Validating skill behavior before deployment
- Running TDD checkpoints on skill development
When NOT To Use
Avoid this command if:
- Evaluating skill quality metrics - use /skills-eval instead
- Creating new skills - use /create-skill instead
How It Works
- Executes RED/GREEN/REFACTOR phases through
superpowers:test-driven-development. - Accepts the same arguments as the previous
/test-skillcommand. - Adds superpowers' reporting and enforcement of TDD checkpoints.
Notes
- Behavior is backward compatible with prior
/test-skillusage. - Use
--phaseto target a single stage or run the full cycle without flags.
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.
- 10d ago First seen · 35 lines · 29 tokens per session scan A bd53e96f8f81
test-skill is a command published in the GitHub repository athola/claude-night-market (337 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 257 once invoked, about $0.0001 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 commands, from other repositories
plan-feature
Production-grade feature planning with dual-AI validation (Claude + Antigravity/Gemini 3 via agy).
dev
(Dev) Full TDD development cycle - from prompt to documented feature. Orchestrates exploration, planning, and execution.
execute
(Dev) Execute an existing development plan using TDD. Resumes from last incomplete test case.
test:first
(Pytest) Create a test BEFORE implementation (TDD red phase).
usage-add
PitWay: Accumulate measured planning or qa token usage onto a milestone.
eval
Evaluate and improve one healthcare agent's system prompt. Run up to 5 iterations of: prepare fixed questions -> answer -> judge -> improve -> re-score -> commit if better.