glm_5_consult_knowledge

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states that this tool is for consultation and not task execution, but does not mention side effects, permissions, rate limits, or output behavior. Important traits like whether the call is read-only or has any safety implications are absent.

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 a single, front-loaded sentence that efficiently conveys the core purpose. It avoids unnecessary words but could benefit from a brief list of key parameters or usage hints without adding much 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?

Given the tool has 8 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on parameter usage, return values, and behavioral constraints, making it incomplete for an agent to use effectively without prior knowledge.

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 8 parameters with 0% description coverage, and the tool description provides no additional explanation for any parameter. For instance, 'domain', 'context', 'outputFormat', 'responseMode', and others are not explained, leaving the agent to infer their meaning from names alone.

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 verb 'consult' and the resource 'GLM' for knowledge purposes. It explicitly lists use cases (expert explanation, second opinion, architecture advice, unfamiliar concept) and distinguishes this tool from task execution, making it easy for the agent to understand its primary function.

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 provides explicit negative guidance ('not task execution'), which helps differentiate from many sibling tools like glm_5_execute_development_task. However, it does not name specific alternative tools for related use cases, missing a direct comparison.

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