Retour Brutal

VérifiéPrudence

Obtenez des critiques brutalement honnêtes et structurées d'idées, plans, code ou propositions via un LLM externe avec des personnalités adversariales.

Spar Skills Guide Bot
DeveloppementIntermédiaire
0023/07/2026
Claude Code
#feedback#critique#adversarial#red-teaming#review

Recommandé pour

Notre avis

Obtient des retours honnêtes et structurés sur des idées, plans, code ou propositions via un LLM externe avec des personas adversaires.

Points forts

  • Critique impartiale et directe grâce à un modèle externe
  • Personas variés (avocat du diable, red team, Gordon Ramsay) adaptés au besoin
  • Prise en compte du contexte (fichiers, code) pour des retours précis

Limites

  • Nécessite une clé API pour le modèle externe (par défaut XAI)
  • Ne génère jamais de critique localement en cas d'échec du script
  • Peut être perçu comme trop dur si on attend des retours constructifs uniquement
Quand l'utiliser

Quand vous avez besoin d'un regard extérieur impitoyable pour identifier les failles d'une idée ou d'un plan.

Quand l'éviter

Quand vous préférez des retours constructifs et équilibrés, ou que vous ne pouvez pas utiliser un LLM externe.

Analyse de sécurité

Prudence
Score qualité90/100

The skill runs Bash commands to execute Python scripts that send user content to external LLM APIs. While the user initiates this and the scripts are within the skill bundle, network exfiltration and API key usage present caution-level risk.

Points d'attention
  • Executes Python scripts via uv run that make network requests to external APIs, potentially exposing user-provided content.
  • Reads environment variables for API keys, which could be mishandled in logs or error output.

Exemples

Critique a business plan
brutal feedback: I want to start a subscription box for left-handed people. Pitch: monthly curated items for lefties. Persona: red team.
Tear apart a code architecture
tear this apart: My microservice design uses event sourcing with Kafka, but I'm worried about complexity. Read the architecture.md file and critique it with Gordon Ramsay persona.
Red team a product idea
red team this: We're building a mobile app that uses AI to generate personalized workout plans. Attack the assumptions and potential failure points.

name: brutal description: Get brutally honest feedback on ideas, plans, code, or proposals from an external LLM. Triggers: "brutal feedback", "critique this", "tear this apart", "what's wrong with this idea", "red team this", or needs honest critical review of an idea or plan. allowed-tools: Bash,Read,Agent,AskUserQuestion

BRUTAL Feedback

Get brutally honest, structured critique of ideas, plans, code, or proposals by sending them to an external LLM (Grok via xAI by default) with adversarial personas and third-party framing.

Prerequisites

  • uv installed (dependencies are auto-installed via PEP 723 inline metadata)
  • For external model mode: XAI_API_KEY environment variable set (or appropriate key for chosen provider)
  • For Claude CLI mode: claude CLI installed and authenticated

Critical Rule

ALL critique content MUST come from the external model via the script. If the script fails or returns no output, report the error to the user. NEVER generate critique content yourself — not as a fallback, not as a summary, not in any form.

Workflow

1. Collect the idea

If $ARGUMENTS contains the idea, use it directly.

If $ARGUMENTS is empty or only contains a persona/modifier, ask:

header: "Idea"
question: "Paste or describe the idea, plan, or proposal you want critiqued."

2. Determine mode

No question needed — detect from $ARGUMENTS before extracting the idea text. Only match these cues when they appear as standalone directives, not embedded inside the idea content:

  • If user says "use claude", "claude cli", or passes a Claude model flag (e.g. --model sonnet-4-6) → Claude CLI mode. Use critique-claude.py.
  • Otherwise → External model mode. Use critique.py.

Do NOT match partial words inside idea text (e.g. "my opus on distributed systems" is not a Claude model cue).

3. Select persona

ALWAYS ask for persona unless $ARGUMENTS contains an explicit persona cue from the table below. Do NOT infer persona from the skill name or tone of the idea.

header: "Persona"
question: "Pick the feedback style."
multiSelect: false
options:
  - label: "Devil's Advocate"
    value: "devil"
    description: "Basic counterarguments, challenges assumptions"
  - label: "Red Team"
    value: "red-team"
    description: "Adversarial weakness hunting, thorough and methodical"
  - label: "Gordon Ramsay"
    value: "ramsay"
    description: "Surgical, no mercy, tears apart what's lazy"

Pass the selected value (not the label) as the --persona argument: devil, red-team, or ramsay.

Explicit cue detection (only these exact phrases skip the question):

| Persona | --persona value | Cues | |---------|-------------------|------| | Devil's Advocate | devil | "devil", "counterarguments" | | Red Team | red-team | "red team", "attack" | | Gordon Ramsay | ramsay | "ramsay", "tear apart" |

4. Gather context (optional)

If the idea references code, files, or domain-specific context, read relevant files and pass as --context to give the external model grounding.

5. Run the critique

Write the idea to a temp file, then run the appropriate script based on mode from step 2.

External model mode:

uv run ~/.claude/skills/brutal/scripts/critique.py \
  --idea-file /tmp/brutal-idea.txt \
  --persona PERSONA \
  [--self-critique]

Claude CLI mode:

uv run ~/.claude/skills/brutal/scripts/critique-claude.py \
  --idea-file /tmp/brutal-idea.txt \
  --persona PERSONA \
  [--model MODEL] \
  [--self-critique]

Pass --model only if the user specified a particular Claude model (e.g. claude-sonnet-4-6). If they just said "use claude", omit --model to use the default.

For both modes: write large context to a file and pass --context-file /tmp/brutal-context.txt. For short ideas, --idea "TEXT" and --context "TEXT" also work. Add --self-critique when the modifier is active.

The script outputs formatted markdown directly. Do NOT reformat, summarize, or rephrase any of it.

6. Present the output

Print the script's stdout verbatim. Do NOT add any text before, after, or around it.

Alternative Providers

When the user specifies an exact model string (e.g. "use gpt-4o"), pass it as --model PROVIDER/MODEL verbatim. When the user gives only a provider name (e.g. "use openai"), use the default model from the table below. Add the required --with extra to the uv run command.

| Provider | Default --model value | --with extra | Env var | Notes | |----------|-------------------------|----------------|---------|-------| | xAI (default) | xai/grok-4.20-0309-reasoning | (built-in) | XAI_API_KEY | | | OpenAI | openai/gpt-5.4-2026-03-05 | (built-in) | OPENAI_API_KEY | | | Anthropic | anthropic/claude-opus-4-6 | instructor[anthropic] | ANTHROPIC_API_KEY | | | Google | google/gemini-3.1-pro-preview | instructor[google-genai] | GOOGLE_API_KEY | | | Ollama | ollama/deepseek-reasoner | (built-in) | — | Defaults to http://localhost:11434/v1. Set BASE_URL in .env to override |

Example with Anthropic:

uv run --with "instructor[anthropic]" ~/.claude/skills/brutal/scripts/critique.py \
  --model anthropic/claude-sonnet-4-20250514 \
  --idea-file /tmp/brutal-idea.txt \
  --persona PERSONA

Behavioural Modifiers

| Behaviour | Cues | Default | |-----------|------|---------| | Claude CLI mode | "use claude", "claude cli", or a Claude model flag (e.g. --model sonnet-4-6) | Off (uses external model) | | External model override | "use openai", "use gemini", "use ollama", "use grok-3" | xai/grok-4.20-0309-reasoning | | Self-critique | "self-critique", "double check", "critique yourself" | Off | | Include code context | references files or code in the idea | Auto-detect |

Keywords

brutal feedback, honest review, critique, red team, devil's advocate, tear apart, roast, what's wrong, poke holes, claude cli

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