evaluate_thought

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not reveal whether this mutates stored state, whether it writes evaluation results to the tree, or what the response contains. The claim that score can be '0-1 or 0-100' actively misleads, since the schema enforces 0-100 only, undermining trust in the description.

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 brief and front-loads the core verb and resource, which is efficient. However, it earns no extra credit for conciseness because one of its few details ('0-1') is inaccurate and the term 'multi-criteria fields' is vague, making the sentence compact but not sharp.

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?

With 7 parameters, 3 required, nested objects, no output schema, and no annotations, this description is too thin to fully guide an agent. It does not explain what criteriaScores represents, how score relates to the optional criteria, whether inputs are persisted, or what success/failure looks like after invocation.

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?

Although the schema has 100% parameter coverage, the description introduces confusion by allowing a '0-1' score scale that the schema contradicts. It also refers vaguely to 'optional multi-criteria fields' without explaining how criteriaScores, risk, creativity, or reasoning map to that phrase, providing no additional clarity beyond the schema.

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 identifies the action ('Evaluate a thought') and the primary resource ('thought'), which distinguishes it from sibling tools like verify_thought or refine_thought at a basic level. The mention of a score and optional multi-criteria fields adds specificity, though '0-1 or 0-100' is ambiguous and conflicts with the schema's 0-100 range.

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 guidance on when to use this tool versus alternatives like verify_thought, select_thought, or self_reflect_thought. It does not state any prerequisites, such as needing an existing tree and thought, nor does it clarify whether this tool is for recording an evaluation versus merely scoring one.

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