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

With no annotations, the description carries the full burden and does disclose the most important behavioral trait: results are normalized frequency scores within an ingested dataset, not absolute volume — a caveat that prevents systematic misinterpretation. It omits other operational context (permission/read-only status, pagination, truncation), but the semantic disclosure is substantive.

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?

Three short sentences, front-loaded with the core action, followed by the interpretation of what the scores mean and the key limitation. No redundant restatement of the name or 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 five-parameter read tool with no output schema, the description covers purpose, entity dimensions, and the meaning of the returned scores, which is the main interpretive risk. It stops short of describing the response shape (field names per company/role/city) or pagination behavior via limit, which would have closed the last gap.

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 baseline is 3. The description reinforces that results are sliced by company/role/city on a weekly basis, but adds no format, defaulting, or interaction detail beyond the schema (e.g., how role interacts with city, or unit of the limit).

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+resource: "Retrieve weekly hiring frequency scores per company/role/city," plus an explicit scope statement that these are share-of-voice signals rather than absolute volume. It does not name a sibling tool it overlaps with (e.g., get_market_summary, get_stats), so differentiation is by concept rather than by routing.

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?

Usage is only implied: an agent can infer this is the tool for relative hiring activity broken down by company/role/city, and the negative clause warns against reading results as market volume. There is no explicit when-to-use vs. alternatives, no prerequisites, and no statement about when another tool is preferable.

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