cerebras_reasoning

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

Discloses model name, parameters, reasoning format hidden. However, no annotations exist, and description fails to mention whether tool modifies state (file_path suggests write), potential costs, or rate limits. Moderate transparency.

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 sentence with two clauses, zero waste, front-loaded with core purpose. Highly concise.

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, but schema covers parameters well. Description focuses on model capabilities; missing output format details, but overall sufficient for usage given sibling comparison and parameter schema.

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 coverage is 100% with detailed descriptions. Description adds no extra information about parameters, so baseline 3 is appropriate.

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 explicitly states verb (generate code), resource (Cerebras zai-glm-4.7), and distinguishes from siblings by emphasizing 'most powerful for deep reasoning' vs other cerebras tools.

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?

Clearly states when to use: for algorithms, architecture decisions, advanced logic, deep reasoning. Implicitly contrasts with siblings, but no explicit when-not-to-use or alternative naming.

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