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

Annotations only declare readOnlyHint=true and openWorldHint=false, so the description must carry the rest — and it does: engine parity with POST /api/ota-link/compute, the free-space-only physics exclusions, that distance and misc loss are user assumptions disclosed on the result, and the caller-asserted labelling triggered by omitting user_request. These are non-obvious behavioral traits that materially affect interpretation of the output.

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 outputs are front-loaded in the first sentence, and the sibling disambiguation is placed last where it belongs. It is a single dense block, and a few clauses (reuse rules, assumption disclosure) duplicate what the schema already states, so it is efficient but not waste-free.

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 13-parameter RF physics tool with no output schema, the description covers everything an agent needs: what is computed, what is excluded from the model, which inputs are reused or defaulted, and the shape of the returned figures. The absent output schema is compensated for by the explicit result enumeration.

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 schema already documents all 13 parameters including the W-vs-dBm preference, defaults, and reuse rules. The description largely restates those (distance and misc loss as 'user assumptions', reuse of sensitivity/gain/frequency) rather than adding new parameter-level meaning, so the baseline 3 applies.

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 ('Compute a one-way over-the-air link budget') and enumerates exactly what the result contains (EIRP, Friis FSPL, received power, link margin, closes/marginal/fails verdict, max range). It explicitly names the sibling it is not ('For the stage-by-stage cascade through one chain's parts ... use run_link_budget instead'), so an agent can route correctly without opening either 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?

Explicitly states when to use this tool versus run_link_budget, names the scope boundary (FREE-SPACE ONLY, excluding rain/terrain/multipath/fading), and documents the fallback behavior when inputs are omitted (sensitivity reused from a prior link budget; tx gain and frequency from a prior antenna design). Nothing about selection is left to inference.

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