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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior. The description adds non-obvious value by distinguishing the data's provenance and freshness: static DOL published files (certified, denied, medians, 12-month filings) versus live pending counts 'right now' and their stage. It does not mention pagination or rate limits, but for a read-only lookup that is minor.

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 dense sentences, front-loaded with the payload and followed by the prerequisite and an example — no filler. The parenthetical enumeration is long but each item earns its place by defining the return shape in the absence of an output 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?

With no output schema, the description must convey return values, and it does so concretely (certified, denied, median days, 12-month filings, median offered wage, pending counts and stage). Combined with the enum kind and the search_sponsors prerequisite, an agent has enough to call it correctly; only minor gaps around error cases or empty results remain.

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 meaning: it supplies a concrete invocation example ({"kind": "employer", "slug": "microsoft-corporation"}) and reinforces that the slug is derived from search_sponsors. It stops short of clarifying edge cases (e.g., singular 'law firm' vs plural), but the added example and provenance note push it above baseline.

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 names a specific resource (PERM records for employers, law firms, or occupations) and enumerates the concrete payload (certified/denied counts, median days to decision, 12-month filings, median offered wage, pending counts by stage). It also distinguishes itself from the sibling search_sponsors, which is the discovery tool that produces the required slug, so an agent can tell the two apart without opening schemas.

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 gives a clear prerequisite — 'Find the slug with search_sponsors first' — which is exactly the sequencing an agent needs. However, it does not draw boundaries against lookup_case or queue_status (other case-level siblings), so an agent must still infer that this is the aggregate profile lookup rather than an individual case lookup.

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