skill

skill is a skill for Claude Code, Codex from Rebel028/gauntlet. It costs 0 tokens per session (796 once invoked), scanned A, original, MIT.

A review method that asks at least two independent critics to attack an idea from different viewpoints. The critics look for problems in areas such as logic, maintenance, user impact, history, and security.

In plain words
What is it for?
Pressure-testing one design, comparing several options fairly, checking assumptions, and finding issues in decisions that would be difficult to undo.
Why use it?
It finds weaknesses before you build or commit to something. It is useful because different reviewers may notice different failure modes, while the reviewers only critique and do not change the code.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/rebel028/gauntlet/skill
Any agent
npx skills add Rebel028/gauntlet --skill skill
Clone the repo
git clone --depth 1 https://github.com/Rebel028/gauntlet

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/rebel028/gauntlet/skill.svg)](https://agentmods.dev/skills/rebel028/gauntlet/skill)
Your own site
<a href="https://agentmods.dev/skills/rebel028/gauntlet/skill"><img src="https://agentmods.dev/badge/skills/rebel028/gauntlet/skill.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 796 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00796
Opus 5 $0.00000 $0.00398
Sonnet 5 $0.00000 $0.00159
Haiku 4.5 $0.00000 $0.00080

Measured 3d ago against content hash c416e8081a05, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 3d 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.

src/skill/SKILL.md · 37 lines

How it starts

The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gauntlet

A bias-check technique: spawn 2+ independent subagents, each attacking the idea from a different angle, to catch the flaw BEFORE it's set in concrete.

The name is the method: you run the idea through a gauntlet of independent attackers, each trying to stop it for a different reason. What makes it out the far side has earned your commitment. When you're choosing between options, run them all through — the one that takes the most hits and survives is usually the answer.

When picking between options rather than vetting one, run each agent against all the options at once ("attack each of these three caching approaches; for each, find where it breaks") so the comparison stays apples-to-apples.

How to run it

  1. Pick 2+ agents with DIFFERENT angles. Not "one for / one against" — that's a weak debate. You want genuinely different optics so the attacks don't overlap. The five standing personas are all read-only (they ground critique in your code but never modify it):

    • gauntlet-formalist — structure, logic, invariants. Are the categories actually orthogonal?
    • gauntlet-practitioner — the year-one maintainer. What gets painful, who gets paged?
    • gauntlet-consumer-advocate — the downstream consumer (API client, on-call). What breaks for them?
    • gauntlet-historian — prior art. Who tried this and why did it break?
    • gauntlet-threat-modeler — security. Where's the abuse case, the blast radius?

    No fit? Use the custom-adversary template (custom-adversary.md, alongside this skill) — not a registered agent; paste it into a general-purpose subagent restricted to read-only tools.

    Pick angles that fit the decision. A migration → formalist + practitioner + historian. An auth change → threat-modeler + consumer-advocate + formalist. Pick the 2–4 sharpest, not all six.

  2. Give each agent the FULL idea: what it is, what's decided, which alternatives were rejected and why, what's irreversible. Without it the attack misses.

  3. Do NOT hint at the conclusion you want. Never write "confirm that X is good." Write "attack X, find where it breaks." A skeptic agent that's been told the desired answer is useless.

Read the full file on GitHub · 37 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 3d ago First seen · 37 lines · 0 tokens per session scan A c416e8081a05

Subscribe to this mod's changes

skill is a skill published in the GitHub repository Rebel028/gauntlet (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 796 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.

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