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roast_cli_debate

Deploy two CLI agents in a structured adversarial debate, anchoring PRO and CON positions extracted from a topic for critical multi-perspective analysis.

Instructions

Deploy 2 CLI agents in structured adversarial debate with constitutional position anchoring. Calling agent should extract PRO/CON positions from topic before invoking. IMPORTANT: Critically evaluate all debate output — positions are assigned, not necessarily held. Weigh each argument's validity independently before presenting to the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesThe debate topic
proPositionYesThe PRO thesis to defend (extracted by calling agent)
conPositionYesThe CON thesis to defend (extracted by calling agent)
targetNoFilesystem path to analyze (e.g., '/path/to/project' or '.'). Directs agents to the relevant part of the codebase.
agentsNoTwo specific debaters to use.
roundsNoNumber of debate rounds (default: 3)
contextNoEssential context for the debate — the substantive background, constraints, and details that shape the argument.
modelsNoModel overrides for specific agents. Codex uses the Codex CLI configured/default model by default unless BRUTALIST_CODEX_ALLOW_MODEL_OVERRIDE=true. Agy is Flash-pinned (no --model flag); field ignored.
context_idNoContext ID for cached pagination or debate continuation
resumeNoContinue debate with a new prompt; omit for pagination/page reads
offsetNo
limitNo
cursorNo
force_refreshNo
verboseNo
mcp_serversNoMCP servers to enable for debate agents (e.g., ["playwright"]). Available: playwright
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Given no annotations, the description carries full behavioral disclosure. It reveals that positions are assigned, not necessarily held, and advises independent evaluation of each argument. This adds important context about the tool's behavior (e.g., potential bias). It does not cover authorization or side effects, but for a debate tool, the disclosed trait is significant.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences that deliver the core purpose, usage guidance, and a critical warning. Every part earns its place, and the most important information (deploying agents, extracting positions) is front-loaded. No redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite a complex schema with 16 parameters including nested objects, pagination, and model overrides, the description only addresses the debate mechanism and the three required parameters. Critical parameters like context_id, resume, offset, limit, models, and mcp_servers are left unexplained. The tool would be difficult to configure correctly based solely on the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 69%, and the description adds value by linking the required parameters (topic, proPosition, conPosition) to the extraction process it advises. However, it does not explain the many other parameters like context, models, or pagination fields. The added semantic guidance for core params is helpful but incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deploys two CLI agents in a structured adversarial debate with constitutional position anchoring. It uses specific verbs ('Deploy', 'extract') and resources ('CLI agents', 'PRO/CON positions'), which distinguishes it from siblings like 'roast'. The purpose is unambiguous and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs the calling agent to extract PRO/CON positions before invoking the tool, providing clear usage direction. It also warns to critically evaluate output, implying when to be cautious. However, it does not explicitly state when not to use this tool or mention alternatives like 'roast', so it lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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