elenchus_evaluate_convergence

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

No annotations are provided, so the description carries full burden. It states the tool returns a prompt (indicates read-only behavior) but does not explain side effects, required permissions, or what 'convergence quality assessment' entails. Behavior is minimally disclosed.

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

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

The description is two sentences long and avoids redundancy. It is front-loaded with the core purpose. However, it could be slightly more informative without adding length.

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

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

No output schema is provided, yet the description only briefly mentions the output is a prompt. It does not explain what the prompt contains, how to use it with sibling tools like elenchus_submit_llm_evaluation, or the context of convergence assessment. This leaves gaps for the agent.

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

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

The input schema has one parameter (sessionId) with a description. Schema coverage is 100%, so the description adds no additional meaning beyond the schema. Baseline score of 3 applies.

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

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

The description clearly states the tool returns an LLM evaluation prompt for convergence quality assessment. It uses a specific verb ('Get') and resource ('LLM evaluation prompt'), but does not differentiate from sibling evaluation tools like elenchus_evaluate_edge_cases or elenchus_evaluate_severity.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives. It implies use for convergence quality assessment but does not mention when not to use it or reference sibling tools.

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