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

Annotations only declare a safe, idempotent read; the description goes well beyond that with the things an agent actually needs: partial and citation-skewed coverage, a 2000-line examination cap with `examined_capped=true` marking a floor, the meaning of `unattributable_in_window`, and the fact that `score` has no documented meaning. It also discloses that near-duplicate grouping and the representative pick are this service's own choices, and that the case-law mirror ends 2026-09-30 — so an empty result is explained rather than misread as absence of authority.

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?

It is front-loaded with the core definition, which is good, but the body is one long paragraph of stacked parenthetical asides and an inline Miranda example (107252 vs 9423233) that is illustrative but expensive. Exact corpus counts like 10,174,547 and 6,561,861 add bulk without changing agent behavior, and the dense punctuation makes it harder to scan than it needs to be.

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 two-parameter read tool with no output schema, the description covers everything that would otherwise be guesswork: what a returned row contains (case name, date, citation_count, group_id, group_size), why rows are grouped, how empty or capped results should be interpreted, and that every response carries `note` and `coverage_note`. Nothing material is left for the agent to infer.

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 earns extra credit by hammering the critical ambiguity that `id` is the DESCRIBED opinion, not the citing one, and by explaining that `limit` counts groups (one representative row per group) rather than raw parentheticals. That grouping/limit interaction is the main semantic trap and it is spelled out.

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 and resource ('returns the one-line parentheticals later courts wrote about that case, verbatim') and pins the input to a single opinion id. It then explicitly separates the tool from neighboring concepts ('not a holding of the described case... not treatment, validity or "good law"'), which lets an agent distinguish it from the sibling treatment and citations tools without opening a schema.

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 clear: call it to see how later courts characterized a case, and go to `treatment` if you want validity/good-law status. It also names `sources` for the full coverage statement and points at `same_case_opinions` / `most_parentheticals_on` for sibling opinions. What's missing is an explicit statement of when this tool should be skipped entirely (e.g., for pre-coverage or uncited cases), though the coverage caveat implies it.

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