fetch_comic_price

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

No annotations exist, so the description must fully disclose behavior. It specifies the data source (eBay) and output fields (min, max, average), which is transparent. However, it omits important details like rate limits, staleness of data, or authentication requirements, leaving gaps for a production tool.

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, front-loaded sentence of 19 words that conveys purpose and output with zero waste. Every word earns its place.

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 explains return values (min, max, average). It lacks currency and time range details but covers the essential functionality. The three parameters are fully described in the 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% (all three parameters described). The description adds no extra meaning beyond the schema; it only mentions return values. Baseline score of 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?

The description clearly states the verb ('Fetch'), the resource ('recent sold prices for a comic book from eBay'), and the output (min, max, average sale price). It distinguishes from sibling tools like 'grade_comic' or 'verify_slab' by its specific focus on pricing data.

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 implies usage for price research but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'collection_value' for portfolio pricing). No when-not-to-use or prerequisite information is given.

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