update_ai_error

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

With no annotations, the description carries full burden. It tags '[mutation]' to indicate a write operation but does not describe side effects, auth requirements, partial vs. full update semantics, or error conditions. It lacks detail on behavioral traits beyond being a mutation.

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 sentence with a tag, which is efficient. It is front-loaded with the purpose and lists changable fields. No extraneous information. However, it could be slightly more structured (e.g., bullet points) but remains 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?

Given no output schema, no annotations, and 4 parameters (3 optional), the description lacks important context such as return values, success/failure responses, or constraints. It does not explain what happens on update (e.g., confirmation, error codes), making it incomplete for a mutation tool.

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%, and the description lists the same fields as the schema (content, category, status). It adds marginal value by summarizing the purpose of each field, but the schema already provides detailed descriptions (e.g., enum values). Baseline 3 as schema does the heavy lifting.

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 'Update an existing AI correction' with verb 'Update' and resource 'AI correction'. It lists the fields that can be changed (content, category, status). However, it does not explicitly differentiate from sibling tools like 'set_ai_error' (which likely creates) or 'delete_ai_error', though 'existing' implies update vs. create.

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 no guidance on when to use this tool versus alternatives like 'set_ai_error' or 'delete_ai_error'. There is no mention of prerequisites, context, or exclusions.

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