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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that prices are live, collected nightly, normalized to USD per milligram, and includes both the true cheapest listing and the cheapest from a vendor with an independently verified COA. This is rich behavioral context beyond a simple 'get prices' statement. It doesn't mention rate limits or failure modes, but for a read-only price lookup, the disclosed behavior is substantial.

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 compact and front-loaded: the first sentence states the core function, the second adds key behavioral details, and the third provides examples. Every sentence earns its place, and there is no fluff or repetition of schema fields.

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 single-parameter read-only tool with no output schema, the description is quite complete. It explains what data is returned (prices per vendor, normalized, with cheapest and verified-cheapest highlights) and the data's freshness. It doesn't specify the exact response format, but without an output schema, that's a minor gap. The example compounds help an agent understand acceptable input values.

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 the schema already documents the 'compound' parameter. The description adds value by giving examples (BPC-157, GHK-Cu, Semaglutide, Retatrutide, TB-500) and clarifying that aliases and slugs are accepted. This goes beyond the schema's generic 'Compound name, alias, or slug' by providing concrete, recognizable instances.

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 function: retrieving live research peptide prices for one compound across all vendors tracked by Peptul, normalized to USD per milligram. It specifies the resource (peptide prices), the scope (all vendors), and the unit normalization, which distinguishes it from generic price tools. It also provides example compounds to anchor the agent's understanding.

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 when to use this tool: when you need current prices for a specific compound across vendors. It doesn't explicitly state when not to use it or name alternatives, but the sibling tools (get_price_history, get_vendor, search_vendors) are contextually distinct. The nightly collection and normalization details give a clear sense of the data's nature, which helps an agent decide if this is the right tool.

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