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roast_cli_debate

Structured adversarial debate between two CLI agents, each anchored to a constitutional position, to analyze code and arguments.

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
limitNo
topicYesThe debate topic
agentsNoTwo specific debaters to use.
cursorNo
modelsNoModel overrides for specific agents. Codex uses the Codex CLI configured/default model by default unless BRUTALIST_CODEX_ALLOW_MODEL_OVERRIDE=true. Agy honors the model label via its native --model flag (1.0.10+).
offsetNo
resumeNoContinue debate with a new prompt; omit for pagination/page reads
roundsNoNumber of debate rounds (default: 3)
targetNoFilesystem path to analyze (e.g., '/path/to/project' or '.'). Directs agents to the relevant part of the codebase.
clientsNoNOT SUPPORTED in debate. Use `agents` to pick the two debaters; custom Claude-routed clients (e.g. GLM) run only via `roast`.
contextNoEssential context for the debate — the substantive background, constraints, and details that shape the argument.
verboseNo
context_idNoContext ID for cached pagination or debate continuation
conPositionYesThe CON thesis to defend (extracted by calling agent)
mcp_serversNoMCP servers to enable for debate agents (e.g., ["playwright"]). Available: playwright
proPositionYesThe PRO thesis to defend (extracted by calling agent)
force_refreshNo
Behavior3/5

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

Without annotations, the description must fully disclose behavior. It reveals that positions are assigned and not necessarily held, which is a key behavioral trait. However, it lacks detail on side effects, costs, or what 'constitutional position anchoring' entails. Some behavioral context is provided, but not comprehensive.

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

Conciseness4/5

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

The description is concise with three front-loaded sentences. The first sentence states the purpose, the second gives an instruction, and the third warns about output interpretation. It wastes no words but could be slightly more structured.

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?

Given 17 parameters, nested objects, and no output schema, the description lacks completeness. It does not explain pagination parameters (cursor, offset, context_id), debate flow, return values, or configuration of agents/models. The schema descriptions help, but the tool description itself is insufficient for full understanding.

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 71%, so the schema already documents most parameters. The description adds no significant per-parameter detail beyond what is in the schema, aside from emphasizing extraction of pro/con positions. This meets the baseline for high coverage.

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's function: deploying two CLI agents in a structured adversarial debate with constitutional position anchoring. This distinguishes it from siblings like 'roast' (likely single-agent) and 'cli_agent_roster' (listing agents).

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 provides specific usage instructions: 'Calling agent should extract PRO/CON positions from topic before invoking' and advises critical evaluation of output since positions are assigned. It does not explicitly mention when not to use or alternatives, but the guidance is clear and actionable.

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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