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propose_subtopics

Generates a structured prompt that instructs an AI to propose sub-topics for a given research cluster, with an optional target count.

Instructions

Build the Phase 1 sub-topic proposal prompt for an AI to consume.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_slugYes
target_countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations exist, and the description does not disclose any behavioral traits (e.g., side effects, memory writes, or safety). The minimal description fails to inform the agent about tool behavior beyond its basic action.

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 a single, well-front-loaded sentence that gets to the point. However, it could benefit from slightly more structure to separate purpose from parameter hints.

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?

With no schema descriptions, no annotations, and incomplete parameter guidance, the description leaves significant gaps. An output schema exists but is not referenced, and the return format is ignored.

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

Parameters2/5

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

Schema description coverage is 0%, and the description offers no explanation of what 'cluster_slug' or 'target_count' mean or how they affect the prompt. The agent must infer from the tool name alone.

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

Purpose4/5

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

The description clearly states the action ('Build') and the resource ('Phase 1 sub-topic proposal prompt'), making the purpose apparent. However, it does not distinguish itself from sibling tools like 'propose_cluster_rebind' or 'propose_research_setup', preventing a top score.

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

Usage Guidelines2/5

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

No indication of when to use this tool vs. alternatives. No context for prerequisites or exclusions is provided, leaving the agent without guidance on selecting it.

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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