glm_5_query_reasoning

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

No annotations provided, so description is the sole source. It mentions 'provider-supported reasoning' but fails to disclose cost, latency, rate limits, or failure behavior. Minimal transparency for a tool that likely involves significant processing.

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?

Single, clear sentence with no extraneous words. However, it could be more structured by front-loading the most critical information (e.g., that this is for deep reasoning, not simple queries).

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 5 parameters, no output schema, and no annotations, the description is too sparse. It does not cover return values, error handling, or typical use scenarios, leaving the agent underinformed.

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?

Schema description coverage is 0%, and the description does not explain any parameter. Parameter names like 'reasoningBudget' and 'comparePerspectives' hint at purpose, but the description adds no value 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?

Description clearly states verb 'resolve' and specifies types of bottlenecks (technical, systems, debugging, etc.). However, it does not differentiate from siblings like glm_5_execute_development_task or glm_5_smart_route, which could also handle similar reasoning tasks.

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?

Implied usage for difficult reasoning problems, but no explicit when-to-use or when-not-to-use. No alternatives mentioned despite many sibling tools with overlapping capabilities.

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