auto_tagging

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

No annotations provided, so the description bears full responsibility for behavioral disclosure. It does not indicate whether the tool is read-only, modifies the database, requires authentication, or has rate limits. The phrase 'automated tag extraction' suggests a read operation, but this is not confirmed.

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 of 20 Chinese characters, efficient and front-loaded with the verb 'extract'. No redundant information.

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, the description should clarify return format or side effects. It lacks guidance on choosing between content and evidence_id, and does not address whether the tool stores tags or just returns them. The tool has 3 parameters with conditional requirements, but the description omits this complexity.

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%, so baseline is 3. The description adds examples of tag types (e.g., research type, disease area) that map to enum values, but does not add depth beyond the schema's minimal descriptions. No explanation of the mutual exclusivity of content and evidence_id.

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 the tool performs automated tag extraction for evidence, with examples of tag categories. It distinguishes from sibling tools that focus on search, summaries, or PDF creation, making its purpose clear.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not specify that content or evidence_id must be provided, or which tag types are appropriate for different scenarios. Users must infer usage from parameter descriptions alone.

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