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

With no annotations, the description carries the full behavioral burden. It does disclose a useful trait — the result cap of 10 — and the resolution-then-price workflow, but says nothing about authentication or rate limits, what happens on zero matches, or whether match quality/ordering is indicated.

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?

Two short sentences, front-loaded with the purpose, followed by the return contract and next step. Every clause 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?

For a single-parameter, no-output-schema tool this covers the essentials: input style, maximum result count, and downstream tool. No-match/empty-result behavior is the only meaningful omission.

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 the baseline is 3, and the description earns a step up by defining the parameter as a 'loose query' with three example formats ('redline ft', 'karambit fade', 'ak47 vulcan') that tell the agent how much precision it can omit. It does not add anything about how partial matches are ranked.

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?

Specific verb ('Find') plus resource ('exact Steam market names of CS2 items') with concrete example queries that define the fuzzy-match scope. It also implicitly distinguishes itself from get_price by framing itself as the name-resolution step that feeds a price lookup.

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?

Explicitly states the usage context: use it with a loose query, then 'pass one to get_price' — a clear handoff to a named sibling. It stops short of stating exclusions (e.g., don't use it when you already have an exact name).

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