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forge-debate
Adversarial multi-model evaluation. Models argue for, against, and neutrally about a subject.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Adversarial multi-model evaluation. Models argue for, against, and neutrally about a subject.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | forge:debate |
| description | Adversarial multi-model evaluation. Models argue for, against, and neutrally about a subject. |
| disable-model-invocation | true |
| argument-hint | [subject: path or proposal or instruction] [--output path] [--code] [--models m1,m2] [--worker model:stance] |
| context | fork |
| effort | high |
| allowed-tools | Bash, Read |
Run an adversarial multi-model evaluation where models argue for, against, and neutrally about a subject.
When invoked from Claude Code, execute the workflow now. Do not just restate these instructions, say "Command completed", or ask the user to run the commands manually unless a real prerequisite is missing.
/forge:debate [subject] [--code] [--models model1,model2]
| Argument | Required | Description |
|---|---|---|
subject | Optional | File, directory, proposal, or instruction on what to evaluate (defaults to cwd) |
--code | Optional | Switch: use code evaluation framework (default: proposal) |
--models | Optional | Comma-separated model list (default: all available) |
--worker | Optional | Repeatable: model:stance or model:"custom prompt" (mutually exclusive with --models) |
--output | Optional | Write result to file instead of conversation (e.g., debate.md) |
Available models: !forge workflow list-models
Only use models with status ready in the table above. If the default set includes unavailable models, pass
--models <ready models> explicitly. If the user explicitly requested an unavailable model, stop and tell them what
proxy or credential is missing rather than silently substituting. If no models are ready, tell the user what's missing
and stop.
Parse $ARGUMENTS into a positional subject and optional flags. The subject is everything that is not a recognized flag
(file path, directory, proposal text, or free-form instruction). Strip any leading @ prefix on the subject. If no
subject is found, default to the current working directory.
Recognized flags (extract from $ARGUMENTS if present):
--code — switch--models <value> — comma-separated model list (mutually exclusive with --worker)--worker <value> — repeatable: model:stance or model:custom prompt--output <path> — write result to file instead of conversationNever ask the user to clarify. If $ARGUMENTS contains anything, proceed immediately.
forge workflow debate "<subject>" [--code] [--models <models>] [--worker <spec>]... --json
Omit any flag the user didn't specify. Do not pass both --models and --worker.
Parse the JSON output. Each model receives a different stance (for/against/neutral) and evaluates the subject from that perspective. If the command fails, surface the real error and stop; do not claim success.
Combine the perspectives:
Make it clear which parts came from agreement across stances versus which parts remain disputed.
Output routing: If --output was specified, write the complete synthesis to that path using the Write tool (create
parent directories if needed). Print a one-line confirmation: Wrote synthesis to {path}. Do not also print the full
result in the conversation. If --output was not specified, print the result in the conversation as usual.
Models are assigned stances cyclically. Default models (from forge workflow list-models):
| Order | Default Model | Stance | Role |
|---|---|---|---|
| 1st | gpt-5.5 | FOR | Supporter -- strengths |
| 2nd | gemini-2.5-pro | AGAINST | Critic -- risks |
| 3rd | claude-opus | NEUTRAL | Analyst -- balanced view |
Use --models to control which models participate. Stances cycle through for/against/neutral in order.
When --code is specified, models evaluate the target code from adversarial perspectives:
forge must be on PATHforge proxy create litellm-openai)Deep single-model analysis of a topic, question, or architectural decision.
Multi-model consensus workflow. Role-assigned models converge toward a shared recommendation through two rounds of evaluation and reconciliation.
Multi-model panel review. Multiple models review independently, then findings are synthesized.
Full Forge QA checklist in Docker container. Use for release validation or comprehensive verification of all Forge features.
Pressure-test a claim, recommendation, or assumption. Defaults to skepticism.
Review design documents, specs, and technical writing for completeness and consistency.