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/gauntlet

Runs a Gauntlet Loop: turns an ambitious goal and optional quality references into a minimal builder/critic prompt judged against a concrete comparison bar, confirms with the user, then executes it as the lead agent until the output beats the bar or the user stops the run — or

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optimus
7419 skills2 agents1 hook
Install
$ npx -y skills add oprogramadorreal/optimus-claude --skill gauntlet --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/gauntlet

Context preview

The summary Claude sees to decide when to auto-load this skill.

Runs a Gauntlet Loop: turns an ambitious goal and optional quality references into a minimal builder/critic prompt judged against a concrete comparison bar, confirms with the user, then executes it as the lead agent until the output beats the bar or the user stops the run — or

SKILL.md

gauntlet.SKILL.md
description: >-
  Runs a Gauntlet Loop: turns an ambitious goal and optional quality references
  into a minimal builder/critic prompt judged against a concrete comparison
  bar, confirms with the user, then executes it as the lead agent until the
  output beats the bar or the user stops the run — or emits it as a
  paste-ready /goal prompt for a fresh session. Use for long-horizon goals
  judged against an inspectable reference. Long-running; spawns many
  subagents, edits project files, and commits finished pieces to a dedicated
  feature branch.
disable-model-invocation: true
argument-hint: "<goal> [possible references or quality bars]"

Gauntlet

Turn an ambitious goal into a builder/critic improvement loop judged against a concrete quality bar, and run that loop until the output wins or the user stops it.

The user's arguments are the goal, plus any references or quality bars they mentioned. If no goal was given, ask for one.

Gauntlet prompts are modeled on Matt Shumer's prompt for the Claude-of-Duty game:

> I want you to build a first-person shooter at the level of the most recent > Call of Duty games. It should be utterly perfect, visually beautiful, with > every single thing done at AAA quality—from textures to physics to anything > you could think of. > > Fan out sub-agents and have sub-agents tackle each one individually so that > the game is utterly perfect. You should /loop on each item and have a > separate sub-agent check it visually to ensure it looks triple A. That > separate sub-agent should be a really harsh critic, and if it doesn't look > triple A, it should keep going. > > Don't stop until each sub-agent is utterly wowed with the quality when > compared with the actual Call of Duty game. It should literally compare them > side by side blind and say which one looks better. Do this in ThreeJS. /loop > until it's utterly perfect. Fan out sub-agents and ultracode.

Copy its register — short, concrete, goal-first, harsh about quality — not its literal tokens. `/loop` and `ultracode` there are one user's shorthand typed into a live session; as commands they mean something else entirely. Never carry slash commands or effort keywords into the prompt you write.

1. Choose the bar

Choose the strongest concrete bar that an agent can actually inspect and compare its work against. If the user has not supplied one, propose a useful comp or measurement that plays the same role for this task that real Call of Duty screenshots played for the Claude-of-Duty game.

Then resolve it into something a fresh agent with no prior context can open: file paths, a URL, a command that renders it, or screenshots saved to disk. A bar that cannot be resolved that way cannot be judged against — say so and fall back to the strongest one that can. Explain the chosen bar in one sentence.

2. Write the gauntlet prompt

Read `$CLAUDE_PLUGIN_ROOT/skills/init/references/constraint-doc-loading.md` and load the docs it lists. The bar defines what "good" means from outside; these define what this project requires from inside. The prompt carries both — the docs as repo paths.

Write a short prompt in that register (minimal is better here — the lead agent decides the specifics).

Give the lead agent the goal and the bar, but let it choose the approach. State the goal as a destination and do not enumerate its aspects, even when the user did: a list of aspects in the goal sentence becomes the decomposition, and that is the lead agent's call. Tell it to divide the goal into the smallest pieces that can be improved and judged independently — a piece is independent only if its builder can work without waiting on or overwriting another builder's files; anything less is merged or sequenced before the pieces are set. One builder takes each piece through every round: it gets the critic's gap verbatim and chooses the fix, which the lead never writes for it. Every round, a separate critic with fresh context judges the piece.

Use the host's available agent capacity; sequence dispatches rather than drop pieces or reviews. Under Codex, disable conversation inheritance for each critic (`fork_turns: "none"` when that option exists), supplying only its frozen remit and resolvable bar/artifact paths. Reuse each piece's builder across rounds. Carry these dispatch rules into the prompt.

Each piece's critic prompt is written once, before its first round, kept on the progress page, and sent every round with only the artifact paths changed. It carries the resolved bar materials themselves — the paths, URL, or command — plus the artifact under judgment, and nothing from the builder: not its report, its reasoning, or its round history. A critic that cannot open the bar grades from memory, which is the builder-grades-itself failure this loop exists to prevent. The lead agent is the other route to that failure, because it reads every builder report and writes every critic prompt: so the remit is never narrowed after a verdict, what a builder found reaches a critic only as a file it can open and measure — never as a conclusion or an exclusion — and a verdict the lead disputes goes to the user as a disagreement, not back to the critic as a new rule.

Critics judge the artifact as a user would meet it — run, rendered, executed — never the builder's summary, and never source review alone when the work is visual or behavioral. Anything presented as computed — metrics, simulation output, live data — must trace to real computation: staged output that merely looks right is a gap, not a pass.

Each critic compares ours against the bar unlabeled — blind A/B when the artifacts allow it, side by side otherwise; never an older and a newer version of our own work, which measures the round, not the bar — and writes its verdict to its own file under `.claude/gauntlet/`, named by piece and round, ending with one of two final lines: exactly **beats the bar**, or the single biggest remaining gap, which goes back for another round. A gap

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Repo: oprogramadorreal/optimus-claude

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