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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered; the description instead adds data-trust semantics the agent could not otherwise know — firm=false means provisional, calibrated_m overrides when present, and every figure carries its own shot count. Those precedence and confidence rules materially change how the agent should present the data. It does not describe response shape or what happens for a player with no recorded shots, leaving a small gap.

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?

Two sentences, front-loaded with the resource description before the usage instruction, and nearly every clause carries distinct information (measurement stats, source precedence, dispersion directions). It is dense to the point of being a run-on, and the shot-count idea is stated twice ('nº de golpes' then 'con el nº de golpes de cada cifra'), which is the main avoidable redundancy.

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?

There is no output schema, so the description must carry the return shape itself — and it does, enumerating distance sources with precedence, per-figure sample sizes, and the two dispersion axes with their categories. Combined with the included guidance on how to act on small samples, an agent has everything needed to call and interpret the tool without further context.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description uses its space on output semantics rather than inventing parameter detail.

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 opens with a concrete resource ('La bolsa del jugador: cada palo con la distancia…') and enumerates exactly what each entry contains: measured median/p25-p80/shot count, hand-entered average_distance, calibrated_m with precedence, plus dispersion toward the pin and from the tee. That is far more specific than the title 'Get bag'. It stops short of naming a sibling (e.g. club_for_distance, which overlaps on per-club distance), so the agent gets no explicit disambiguation signal even though the content is unmistakably distinct.

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 an explicit trigger condition with real user phrasings ('el driver se me va a la derecha', 'me quedo corto con los hierros') and prescribes what to do with the result: cross the felt complaint against measured data for that club, cite the shot count, and say so in half a sentence if the sample is small or the two don't match. That is unusually actionable guidance. It lacks a 'do not use when' clause and never names an alternative tool for related distance questions, which keeps it from a 5.

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