model_metadata_fetch_civitai

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

With no annotations provided, the description carries full burden. It declares the tool is 'READ-ONLY' and 'WITHOUT writing anything,' and adds behavioral context such as how adult models resolve and how to mine example prompts for the trigger. This goes beyond simple read-only disclosure.

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 dense but every sentence adds value. It is front-loaded with the main purpose and includes critical usage instructions. Despite length, it earns its space with actionable guidance.

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?

The description fully covers what the tool does, the data it returns (listing each field), and when to use it. Since there is no output schema, the description adequately explains the return values and provides complete contextual guidance.

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 100%, so baseline is 3. The description does not provide additional meaning beyond the schema's parameter descriptions; it only mentions the tool's overall function. Therefore, it neither adds nor detracts from parameter clarity.

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 the tool's purpose: 'READ-ONLY: pull this model's data from Civitai' and enumerates the specific data fields retrieved (rich description, trainedWords, example prompts, tags, nsfw flag, source_url). It explicitly distinguishes from the sibling tool 'model_metadata_propose' by instructing to call it afterward.

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 when-to-use guidance: 'Call this when the embedded metadata is thin ... or to flesh out details before proposing.' It also instructs to treat the result as raw input and to clean up and call 'model_metadata_propose' afterwards, clearly differentiating usage from alternatives.

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