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

With no annotations, the description carries the full burden and does so well: it discloses that prices are hand-maintained, go stale silently, are automatically withheld from serving on threshold breach, and that the registry never overwrites the price value. Missing only return-shape and permission details, which is a modest gap.

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?

Four tight sentences, front-loaded with what the tool does, then the behavioral caveats, then the usage trigger. No filler and nothing repeated from the schema.

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 read-only audit tool with no annotations and no output schema, the description covers purpose, mechanism, side effects and usage triggers. It stops short of describing the shape of the returned findings, which an agent would have to discover at call time.

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. The description adds genuine meaning by tying the threshold to the withholding mechanism ('a price that disagrees with the registry by more than the threshold'), clarifying intent beyond the schema's 'minimum % difference to report'.

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?

States a specific verb and resource: auditing this server's own pricing data against an external reference registry. An agent can immediately distinguish it from siblings like get_all_pricing or get_data_quality, which just read data rather than compare it against an external source.

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?

Gives explicit trigger conditions: 'Use when the user asks whether the pricing data is accurate or up to date, or wants to audit a specific provider's rates.' It does not name a competing sibling tool to redirect to, but the context is clear enough to select correctly.

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