get_ai_errors

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

The description reveals that the tool lists only 'active' corrections and scopes them to 'this assistant', adding useful context beyond the name. However, with no annotations, it does not disclose other behaviors like pagination, authentication needs, or read-only nature.

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, front-loaded with the main purpose and usage guidance. The stray '[query]' at the end is slightly distracting but does not significantly reduce clarity.

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?

For a simple list tool with two optional parameters and no output schema, the description covers the essential usage. It lacks details on return format or pagination, but the context is sufficient for basic use.

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 for each parameter. The description reinforces usage but does not add new information beyond what the schema provides, resulting in a baseline score.

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 'List active AI corrections for this assistant', specifying the verb (list) and resource (AI corrections). It differentiates from siblings like 'get_customer_ai_errors' by indicating it is per-assistant.

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 guidance: 'To list ALL corrections, pass no parameters. Only use category or query when filtering specific results.' This clarifies when to use each parameter. However, it does not explicitly mention alternatives like 'get_customer_ai_errors'.

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