gauntlet-loop
Skill9 starsChanged 4 months agoNo licenceView on GitHub
Run iterative build-critique loops that push AI output past "good enough" toward a concrete quality bar. Give a lead agent a goal and a real reference to compare against. The agent decomposes the goal into the smallest independently-improvable pieces, assigns each piece a builder and a separate critic with fresh context, and loops until the output matches or exceeds the bar. Use when the first draft is never good enough — games, websites, product design, writing, marketing campaigns, code, research, or anything where output can be inspected and improved.
20 other projects use a version of this.
Adopted by
Most recently taken up by
- celestialdust/achilles-skillstheir own version, first seen Nov 1, 2026
- rubenmarcus/agent-skillstheir own version, first seen Nov 1, 2026
- mblanc/mb-skillstheir own version, first seen Oct 20, 2026
- harshsinghmp/muse-skillstheir own version, first seen Oct 15, 2026
- sreejithraman/SreeStacktheir own version, first seen Oct 15, 2026
- AVANT-ICONIC/skillstheir own version, first seen Oct 13, 2026
Used with
Projects with it also use codebase-design, research and 3 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
GoogleSkillcodebase-design
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Also in 3 projects that use this
NVIDIASkillresearch
Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.
Also in 4 projects that use this
MicrosoftSkillhandoff
Compact the current conversation into a handoff document for another agent to pick up.
Also in 5 projects that use this
- GoogleSkill
grilling
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
Also in 3 projects that use this
- +1 more from google
Other versions20 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 20
- duolahypercho/gauntlet-loop★ 157same name
- emaraschio/cursor-commands★ 9same name
- NicholasSpisak/gauntlet-loop★ 4same name
- protonspy/spec-claude-code★ 4same name
- trilwu/gauntlet-loop-skills★ 3same name
- Kohulan/orthonym-skills★ 2same name
- rubenmarcus/agent-skills★ 2same name
- alexanderpino/skills★ 1same name
- celestialdust/achilles-skills★ 1same name
- emernuness/gauntlet-loop-skill★ 1same name
10 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- design-inspirationSkill
- design-visual-experiencesSkill
- ecosystem-mappingSkill
- finding-unknownsSkill
- graph-maxSkill
- handoff-specSkill
- problem-miningSkill
- spec-goalsSkill
- workspace-osSkill
The file
We split this skill into the rules it gives an agent
10 rules. 0 are common, 10 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 20 edited versions we read keep these.
10
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 20 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
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Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.