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

Annotations cover the safety profile (readOnly, non-destructive, openWorld), and the description goes well beyond that: it discloses the freshness caveat (trailing 180-day re-pull window; older cases may lag the source), the split between server-side indexed filters and client-side post-filtering over a widened window, and the fact that source_url is always current. This is exactly the kind of behavioral context annotations cannot carry.

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?

Purpose and triggering contexts are front-loaded, then grammar, then caveats — a sensible order for a dense tool. It is long and a few clauses (e.g., the 'Pure-publisher posture' editorial) are near-filler, but given 12 parameters and no output schema most sentences carry necessary information.

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 12-parameter, zero-required, no-output-schema tool, the description supplies what the structured fields omit: what each record family contains (eligible_voters, certified_representative, unit_sought), how filters interact, and how fresh the data is. An agent has everything needed to build a correct query and interpret the 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 already 100%, so the baseline is 3, but the description adds real meaning: the {region}-{type}-{sequence} case-number format, what the middle code signifies, and the important caveat that the `name` field (matched by employer_name substring) is usually the employer but the union on CB/CC charges. It also explains which filter combinations the server-side indexes actually support, which the schema only hints at with 'Client-side filter'.

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 opening sentence names a specific verb (Returns) and resource (NLRB case filings) and immediately scopes it to two concrete families (ULP charges and representation/election petitions). It is unmistakable against siblings like get_osha_enforcement or get_enforcement_actions because it defines the domain, the case-number grammar, and the record families.

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?

The 'Use this when the user asks about: union organizing... labor disputes or ULP charges... decertification efforts... a company's labor-relations record' clause gives clear triggering contexts. It stops short of naming alternatives (e.g., unified_search) or stating when NOT to use it, so it is strong context without explicit routing/exclusions.

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