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

With no annotations, the description carries the full burden and does well: it discloses the pay-per-call cost ($0.001 USDC on Base), the payment protocol and the exact failure mode an unpaid call produces (a 402 challenge). It also enumerates the return payload (names, courts, dates, citations, snippets, links). It omits pagination behavior, result caps, and whether a failed/402 call is still billed.

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 sentences, zero waste, correctly front-loaded: what it searches, what comes back, what it costs and how payment surfaces. The pricing sentence is unusual but earns its place because a 402 response would otherwise look like an error.

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?

No output schema exists, and the description compensates by listing returned fields, which is good. But for a search tool with a same-named sibling and no annotations, it should cover pagination/result limits and query/court parameter conventions; those gaps leave an agent unable to call it correctly or choose it confidently.

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 description coverage is 100%, so the two parameters are already documented structurally, and the baseline is 3. The description adds no semantics for 'q' (query syntax, boolean support, natural language vs terms) or 'court' (expected court identifier format), which are the two things an agent would most likely get wrong.

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 and resource ('Search US case law') plus the underlying data source (CourtListener / Free Law Project), which tells the agent what corpus is being hit. It does not distinguish itself from the sibling 'caselaw_search', whose name implies an overlapping function, so the agent cannot tell the two apart from the description alone.

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 description never says when to use this tool rather than the near-identically named siblings caselaw_search or caselaw_fetch, nor does it give any exclusions or prerequisites. The only decision-relevant hint is the per-call price, which an agent could use to prefer a free alternative, but that inference is left implicit.

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