gauntlet-loop

gauntlet-loop is a skill for Claude Code from trilwu/gauntlet-loop-skills. It costs 227 tokens per session (2,153 once invoked), scanned A, original, MIT.

A general method for producing work through repeated building, independent criticism, and revision. It can be applied to coding, writing, design, data, research, prompt engineering, and detection work.

In plain words
What is it for?
Breaking a large goal into reviewable parts, assigning builders and critics, and iterating until the work meets the chosen standard.
Why use it?
It separates making the result from judging it, so an independent critic can check it against a predefined quality bar. It requires an agent system that can use tools and, for a true blind review, run a separate clean context.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents; mentions Claude Code; mentions Codex.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is **Origin:** the Gauntlet Loop method is **Matt Shumer's**, from *"How to Run a Gauntlet Loop"* (https://somethingbig.ai/gauntlet-loop), with the companion repo .

Part of the gauntlet-loop plugin — 2 skills shipped together

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/trilwu/gauntlet-loop-skills
agentmods
npx agentmods add skills/trilwu/gauntlet-loop-skills/gauntlet-loop

Made for: Claude Code.

Or install gauntlet-loop, the plugin that ships this one along with the rest of its 2 skills.

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 gauntlet-loop

README.md
[![agentmods](https://agentmods.dev/badge/skills/trilwu/gauntlet-loop-skills/gauntlet-loop.svg)](https://agentmods.dev/skills/trilwu/gauntlet-loop-skills/gauntlet-loop)
Your own site
<a href="https://agentmods.dev/skills/trilwu/gauntlet-loop-skills/gauntlet-loop"><img src="https://agentmods.dev/badge/skills/trilwu/gauntlet-loop-skills/gauntlet-loop.svg" alt="Measured on agentmods" height="20"></a>
Per session 227 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,153 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 5.1 $0.00227 $0.02153
Opus 5 $0.00113 $0.01077
Sonnet 5 $0.00045 $0.00431
Haiku 4.5 $0.00023 $0.00215

Measured 6d ago against content hash ad913e43b34b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

gauntlet-loop 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.

skills/gauntlet-loop/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gauntlet Loop — core skill (domain-agnostic)

A disciplined loop for producing high-quality work in any domain: build → blind critique → revise → repeat, against a bar the agent cannot talk its way past. Coding, writing, design, data, research, prompt engineering and detection all use the same loop — they differ only in how you pick the bar, what the critic inspects, and the checklist. Those live in references/domains/.

Origin: the Gauntlet Loop method is Matt Shumer's, from "How to Run a Gauntlet Loop" (https://somethingbig.ai/gauntlet-loop), with the companion repo mshumer/Claude-of-Duty. This skill is an independent, attributed adaptation — see ../../CREDITS.md.

Prerequisite: a real agent harness

This loop requires an agentic harness that can open files, run code, render output, take screenshots, call tools, and spawn sub-agents with their own clean context (Claude Code, Cowork, Codex, or equivalent). A single-turn chat cannot produce an independent blind critic — if you can only reply in one context, say so and fall back to a single self-review pass instead of pretending the loop ran.

For large multi-agent runs, use the harness's parallel-agent facilities (in Claude Code: sub-agents, or /ultracode when available).

The four pillars

  1. A bar the agent cannot argue around. The strongest form: the artifact must match or beat something real — a reference implementation, a test suite, a top product's screenshot, a model essay, an eval set, an ATT&CK technique, a working PoC. The bar may be aspirational: it does not have to be realistically reachable. An unreachable bar keeps the loop pulling upward instead of stopping at "good enough".
  2. Give the goal, not the implementation. State what the finished thing must achieve; let the agent choose the route. Prescribing architecture replaces the model's judgment with yours and caps the result at your imagination.
  3. Let the agent split the work. The lead breaks the goal into the smallest pieces that can be improved and graded independently. Independent pieces can run as parallel loops.
  4. The builder never grades itself. The builder and the judge are different agents with separate context. The critic is blind to the builder's reasoning and inspects the real artifact — running code, rendered pixels, actual test output — never the builder's summary.

Read the full file on GitHub · 116 lines

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. 6d ago First seen · 116 lines · 227 tokens per session scan A ad913e43b34b

Subscribe to this mod's changes

gauntlet-loop is a skill published in the GitHub repository trilwu/gauntlet-loop-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 227 tokens to every session and 2,153 once invoked, about $0.0011 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 2026-08-31.

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