gauntlet-loop
Skill2 starsChanged 45 days agoMITView on GitHub
Writes one short, paste-ready prompt that makes a fresh agent loop a builder against a separate harsh critic until the output beats a named, fetchable reference, and can run it on request. Use when the user wants an agent to grind on a goal until it beats a named reference — triggers on "/gauntlet-loop", "gauntlet loop", "gauntlet this", "make a gauntlet prompt", "loop until it beats X", or "make it as good as [named thing]". Applies to builds, writing, code, research, and design goals alike. Not for a metric-driven accuracy loop on an eval split (use eval-loop).
20 other projects use a version of this, 4 of them edited.
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 2 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
GoogleSkillgrilling
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 · 4
- protonspy/spec-claude-code★ 411% same
- mauriciovieira/skills★ 187% same
- sugarrushdev/skills★ 192% same
- FkennedyFox/claude-skills★ 092% same
Wrote their own version · 16
- duolahypercho/gauntlet-loop★ 157same name
- emaraschio/cursor-commands★ 9same name
- sidneyswift/skills★ 9same name
- NicholasSpisak/gauntlet-loop★ 4same name
- trilwu/gauntlet-loop-skills★ 3same name
- rubenmarcus/agent-skills★ 2same name
- alexanderpino/skills★ 1same name
- celestialdust/achilles-skills★ 1same name
- emernuness/gauntlet-loop-skill★ 1same name
- harshsinghmp/muse-skills★ 1same name
6 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 repository22 other files it gives its agents.
- bounded-goalsSkill
- change-asserted-valueSkill
- check-targetSkill
- cluster-failuresSkill
- councilSkill
- enumerate-firstSkill
- eval-loopSkill
- fable-reviewSkill
- handoffSkill
- kickoffSkill
- promo-videoSkill
- prove-invariantSkill
- refusal-censusSkill
- reuse-before-rerunSkill
- run-evalSkill
- run-gateSkill
- scientific-posterSkill
- spy-siteSkill
- test-gateSkill
- understand-before-mergeSkill
- verify-sourceSkill
- watching-background-jobsSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 6 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 20 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 19
If they say run it, you become the lead agent and follow the prompt you just wrote.
- Distinctive: line 42
When you propose bars, prefer the hardest one the agent can genuinely reach.
- Distinctive: line 44
If the goal has a measurable half (load time, token cost, benchmark score, word count, pass rate), name it alongside the bar.
- Distinctive: line 69
Add a budget or cost ceiling line only if the user named one.
- Distinctive: line 70
Add tool names only if the goal needs them (image or video generation, a browser, a deploy target).
- Distinctive: line 133
Over-specifying: Every extra instruction is one fewer decision the agent makes with its own judgment.
“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.
Files
Gauntlet Loop
The user gives a goal. You give back one short prompt they can paste into a fresh agent session.
You are not doing the work. You are writing the prompt that makes another agent grind on the work until it beats a real reference.
Flow
- Read the goal. One line restatement in your head, not on screen.
- Set the bar (the named reference to beat). If the user supplied one, use it. If not, offer 2 or 3 candidate bars, one line each, and stop. Wait for their pick. Do not write the prompt yet.
- Write the prompt. One block, paste-ready, no preamble, no headings inside it, no narration after it.
- Offer to run it. One flat line under the prompt: "I can run this here." Not a question.
If they say run it, you become the lead agent and follow the prompt you just wrote.
The bar is the whole trick
Everything else in a gauntlet loop is scaffolding. The loop only produces quality if the thing it compares against is real.
A bar has to pass three tests:
- Named. A specific thing, not a category. "Stripe's pricing page" works. "Award-winning SaaS sites" does not.
- Fetchable. The critic can actually get it - screenshot the live page, read the published piece, run the binary, open the repo, watch the footage. If the agent cannot obtain it, it will hallucinate the comparison.
- Comparable. Both can sit side by side and a judge can pick one. If you cannot imagine the A/B, it is not a bar.
Bars by goal type:
| Goal | Bar that works |
| Website, app, UI | The live site of a specific best-in-class product, screenshotted at the same viewport |
| Game, 3D, visual | Real footage or screenshots from a named shipped title |
| Writing | A specific published piece by a named author or publication, same length and format |
| Code, tooling | A named repo's implementation, plus its benchmark or test suite as the measurable half |
| Research, analysis | A named analyst report or a paper's methods section, judged on rigour and coverage |
| Deck, doc, deliverable | A real artifact from a firm known for it, same page count |
When you propose bars, prefer the hardest one the agent can genuinely reach. A bar that is too easy makes the loop exit on round one.
If the goal has a measurable half (load time, token cost, benchmark score, word count, pass rate), name it alongside the bar. Taste plus a number beats taste alone.
Prompt template
Adapt the wording every time. Fill the brackets, keep it short, keep the last line.
Build [GOAL].
The bar is [BAR]. Get the real thing first and compare against it directly, not against a description of it.
Break this into the smallest pieces that can be improved and judged on their own. For each piece, fan out a builder and a separate critic with fresh context. The critic inspects the actual output, puts it next to the bar blind with the labels stripped, says which one is better, and names the single biggest remaining gap. Then it goes back to the builder.
The critic should be a harsh critic. Praise is not useful. If ours does not win, it keeps going.
/loop on each piece until the critic picks ours blind. Do not stop before that.
Keep a live progress page updating as the work evolves so I can watch it.
Fan out subagents and ultracode.Rules for what you fill in:
- Bake the bar in as a concrete, fetchable thing. URL, product name, repo, title.
- Add a budget or cost ceiling line only if the user named one. No default cap.
- Add tool names only if the goal needs them (image or video generation, a browser, a deploy target).
- Everything else stays out. No architecture, no file layout, no decomposition, no round count, no stack choice unless the user demanded it. The agent decides those, and it decides better than a spec written before the work started.
Length and voice
Short. Around 120 to 180 words. If the prompt needs a heading to stay readable, it is too long.
Plain sentences. No bullet lists inside the prompt. It should read like someone telling an agent what perfect looks like and refusing to accept less.
Portability
/loop and ultracode are Claude Code features. /loop reruns the prompt on an interval or lets the model pace itself. The keyword ultracode in a prompt a person types or pastes makes Claude run that task as a workflow (multi-agent orchestration); a -p prompt or a scheduled task does not trigger it, and /effort ultracode turns it on for a whole session.
For any other agent, swap the /loop line and the last line for: "Keep looping until the critic picks ours. Run the builders and critics as parallel subagents." The structure carries over unchanged.
Two filled examples
Visual goal. User: "landing page for my running brand, athletic, green and dark, has to feel alive."
Bars offered: A) Nike's current running campaign page B) On Running's homepage C) Gymshark's product landing page. User picks A.
Build a landing page for a running brand. Athletic, peak performance, green and dark, energetic, aimed at a young healthy audience. It needs to be interactive and visually unmistakable.
The bar is Nike's current running campaign page. Screenshot it at desktop and mobile and compare against those directly, not against a description of them.
Break this into the smallest pieces that can be improved and judged on their own - hero, motion, type, colour, imagery, interaction, mobile. For each piece, fan out a builder and a separate critic with fresh context. The critic opens the real page in a browser, puts our screenshot next to Nike's blind with the labels stripped, says which is better, and names the single biggest remaining gap. Then it goes back to the builder.
The critic should be a harsh critic. Praise is not useful. If ours does not win, it keeps going.
/loop on each piece until the critic picks ours blind. Do not stop before that.
Keep a live progress page updating as the work evolves so I can watch it.
Fan out subagents and ultracode.Non-visual goal. User: "a 2000-word explainer on vector databases for non-engineers."
Bars offered: A) a specific Stripe engineering blog explainer B) a named Julia Evans post C) the Wikipedia article plus a comprehension test. User picks B.
Write a 2000-word explainer on vector databases for readers who are smart but not engineers.
The bar is Julia Evans' writing on hard technical topics. Pull three of her actual posts and compare against them directly, not against a description of her style.
Break this into the smallest pieces that can be judged on their own - the opening, each explanation, the diagrams, the analogies, the ending. For each piece, fan out a writer and a separate critic with fresh context. The critic reads ours and hers blind with the bylines stripped, says which one a non-engineer would understand faster, and names the single biggest remaining gap. Then it goes back to the writer.
The critic should be a harsh critic. Praise is not useful. If ours does not win, it keeps going.
/loop on each piece until the critic picks ours blind. Do not stop before that.
Keep a live progress page updating as the work evolves so I can watch it.
Fan out subagents and ultracode.What breaks a gauntlet loop
- A vague bar. The critic invents a comparison and approves everything. Most common failure by far.
- The builder judging its own work. The critic must be a separate agent with fresh context. It should not know how hard the builder tried.
- A soft critic. Say "harsh" in the prompt and give it a binary job: which one is better, A or B. Scores out of 10 drift upward every round.
- Named exit after N rounds. The exit is winning the comparison, or the user stopping the run. Never a round count.
- Over-specifying. Every extra instruction is one fewer decision the agent makes with its own judgment. Minimal wins.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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.
Now do this for your own.
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.

