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/gauntlet)<a href="https://agentmods.dev/commands/athola/claude-night-market/gauntlet"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/gauntlet/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/gauntlet"><img src="https://agentmods.dev/badge/commands/athola/claude-night-market/gauntlet.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 | $0.00017 | $0.00103 |
| Opus 5 | $0.00009 | $0.00051 |
| Sonnet 5 | $0.00003 | $0.00021 |
| Haiku 4.5 | $0.00002 | $0.00010 |
Grade A, and why
gauntlet 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 7d 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
Gauntlet Challenge Session
Invoke Skill(gauntlet:challenge) to run a 5-question session.
Arguments:
- No args: random scope, 5 questions
--count N: run N questions--scope <file-or-dir>: limit to specific files--type <type>: force a specific challenge type
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.
- 7d ago First seen · 16 lines · 17 tokens per session scan A b83c541fa99f
gauntlet is a command published in the GitHub repository athola/claude-night-market (337 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 103 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 2026-09-03.
Other commands, from other repositories
teach-me
Interactive voice-narrated tutorial on the current conversation topic (or a named one) — ASCII diagrams, spoken lesson content, one question per beat, quizzes. Routes to the Teach skill's Teach workflow. USE WHEN /teach-me, teach me, tutorial, quiz me, learn mode. NOT FOR plain written explanations with no dialogue…
skip-reflect
Discard queued learnings without processing.
setup
Verify ClauDex prerequisites — Codex CLI, authentication, and git.
view-queue
View the learnings queue without processing.
modes
Detailed guide to pair programming modes and their optimal use cases.
daily-okr
Run a daily knowledge compound loop (7 KR). Invoke with /daily-okr or "start my daily review".