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KohulanKohulan/orthonym-skills/skills/gauntlet-loop/SKILL.md

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

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.
  • GoogleSkill

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    Also in 3 projects that use this

  • NVIDIASkill

    research

    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.

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    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

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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
  1. Distinctive:

    If they say run it, you become the lead agent and follow the prompt you just wrote.

    line 19
  2. Distinctive:

    When you propose bars, prefer the hardest one the agent can genuinely reach.

    line 42
  3. Distinctive:

    If the goal has a measurable half (load time, token cost, benchmark score, word count, pass rate), name it alongside the bar.

    line 44
  4. Distinctive:

    Add a budget or cost ceiling line only if the user named one.

    line 69
  5. Distinctive:

    Add tool names only if the goal needs them (image or video generation, a browser, a deploy target).

    line 70
  6. Distinctive:

    Over-specifying: Every extra instruction is one fewer decision the agent makes with its own judgment.

    line 133

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

  1. Read the goal. One line restatement in your head, not on screen.
  2. 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.
  3. Write the prompt. One block, paste-ready, no preamble, no headings inside it, no narration after it.
  4. 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:

GoalBar that works
Website, app, UIThe live site of a specific best-in-class product, screenshotted at the same viewport
Game, 3D, visualReal footage or screenshots from a named shipped title
WritingA specific published piece by a named author or publication, same length and format
Code, toolingA named repo's implementation, plus its benchmark or test suite as the measurable half
Research, analysisA named analyst report or a paper's methods section, judged on rigour and coverage
Deck, doc, deliverableA 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.

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