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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed world), so the added value is the disclosure that this returns only ids/titles/URLs and requires a follow-up fetch — a genuinely useful behavioral trait. It does not mention limits on result count or ranking, but the core workflow behavior is disclosed.

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?

A single compact sentence covering purpose, output, follow-up step, and the alternative path — nothing redundant. The phrasing 'Id search for deep-research clients' is slightly compressed/jargony, which costs a point on readability.

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 one-parameter lookup with an output schema and full annotation coverage, the description supplies what matters: the discovery-then-fetch pattern and the alternative path. Missing only the scope of the underlying corpus and any result-limit expectations.

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% and the schema already gives example queries and length bounds, so the parameter is fully documented without the description. The description adds no guidance on query formulation, so baseline 3 applies.

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 states the operation is an ID search and specifies the return shape (ids, titles, URLs), and it distinguishes itself from the named tools by role (ID discovery vs. direct answers). It never says what corpus is being searched, leaving the title ('legal-marketing records') to carry that, so it falls short of fully self-contained clarity.

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?

It sets up a clear two-step workflow (search here, then read with fetch) and signals when not to use it: 'the named tools answer one question directly.' The reference to 'named tools' is collective rather than naming specific siblings like search_rules, search_ethics_opinions, or data_search, so the agent must infer which alternative applies.

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