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

Annotations only establish that this is a safe, idempotent read; the description adds substantial behavioral context beyond them: approximate payload sizes per depth, the 25-job cap with a 'truncated' flag, unknown_category/unknown_platform responses for bad ids, that branch queries carry no totals, and that depth is incompatible with topic.

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?

Front-loaded with the purpose and every clause carries useful detail (sizes, caps, error ids), but the density of nested parentheticals makes it a single packed block that is harder to scan than it could be. No genuinely wasted sentences, so only a small deduction.

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?

There is no output schema, so the description must carry the return-value burden, and it does: it enumerates the count fields, explains null pricing, describes the truncation flag, and specifies the error-shaped answers for unknown ids. An agent has everything needed to call it and interpret results.

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, but the description adds real cross-parameter semantics the schema lacks: depth defaults change depending on whether category/platform is supplied, depth is not valid with topic, and what each value actually returns. It stops short of exhaustively restating each parameter, which 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?

States a specific verb+resource (overview of the data API catalog) and then precisely defines the resource's shape: categories > platforms > jobs with counts at every level. It is clearly distinguishable from siblings search_catalog, discover, and search, which it explicitly positions itself as a precursor to.

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 usage branching: no arguments = summary, depth platforms/jobs/full for more, category or platform to scope a branch, topic for keyword jobs. It also names the alternatives and when to move on ('Follow up with search_catalog or discover to pick an endpoint for a job').

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