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

Annotations only declare non-readOnly, non-destructive, non-idempotent, closed-world; the description adds substantial context the annotations do not: this is a demo whose output is an AI draft with no professional validation, that nothing is charged and nobody is contacted, and the exact branching logic (all fields match vs any field differs vs no entry). This is well beyond what structured fields convey.

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 the demo disclaimer are front-loaded, and each sentence carries information (demo nature, fill-the-fields rule, branch outcomes, quote flow, exclusions). It is dense and reads as a run-on in places, with the no-real-data warning appearing twice across description and schema, but nothing is padding-grade.

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 an 11-parameter, nested-object tool with no output schema, the description carries the burden well: it describes both return shapes (draft with assumptions, sources and validity window; or sample price band and turnaround), the free/uncontacted guarantee, and the eligibility limits. Nothing an agent needs to decide whether and how to call it is missing.

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 91%, so the baseline is 3, but the description adds real meaning: it enumerates the intake fields that actually drive matching and states that only those fields (never the free-text question) are used. Minor flaw: it names `cross_border` and `already_filed`, which do not appear in the intake schema, so the field list is slightly imprecise.

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+resource (ask a Swiss tax question for a business or freelancer) and describes the two outcome paths precisely: an exact-match draft entry, or a sample indicative price band and turnaround. It also implicitly separates itself from `commit` ("Free: nothing is charged") and names `status` as the sibling that shows sample quotes.

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?

Gives explicit when-not guidance ("Do not use for private matters or for countries other than Switzerland, and send no real personal data") plus a concrete instruction for how to trigger quotes ("call `ask` again with `request_quotes: true") and how to inspect them via `status`. The matching rule ("matching uses these fields only, never the question text") doubles as a usage constraint.

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