audit_fpl_players

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real value by disclosing the exact analytical payload returned, which matters because there is no output schema. It does omit what happens with unknown or ambiguous player names, which is the main remaining behavioral 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?

A single dense sentence with the resource and the use case front-loaded, followed by the metric list. Every enumerated metric is informative rather than filler, so the length is justified, though the parenthetical metric list is slightly harder to scan than a short bulleted structure would 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 one-parameter aggregator with no output schema, the description does the necessary work by naming the returned fields. What is missing is failure behavior for unresolvable names and whether results are returned in input order, which an agent would need to interpret the response correctly.

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% and there is a single well-described 'players' array, so the schema carries the load; the description's inline example ('Haaland', 'Saka') merely echoes the schema's own example. It adds no guidance on name-matching tolerance or whether full names vs. surnames are accepted.

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 gives a specific verb ('Audit') and resource ('a list of FPL player names') and enumerates exactly which metrics are produced (Start %, FDR, injury flags, suspension risk, set-piece duties, ep_next). This makes the aggregating nature clear against siblings like get_injuries or get_set_piece_takers, though it never explicitly says how it differs from chaining those tools.

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 implied through concrete scenarios ('a user's 15-man squad or transfer shortlist'), which tells an agent the intended context. However, there is no explicit when-not guidance and no mention of the sibling tools an agent might otherwise call for the same underlying data.

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