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

The annotations already establish read-only, idempotent, non-destructive behavior, so the description's main added value is disclosing that these are AI predictions and listing the returned elements: Starting 11, formation, starter likelihoods, bench options, and manager notes. It does not discuss freshness, model limitations, or reliability, which would have made it richer.

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?

The description is a single front-loaded sentence with no filler. Each phrase contributes either the tool's action, the prediction source, or the returned content.

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 low-complexity, one-parameter tool with no output schema and strong safety annotations, the description is largely complete because it enumerates the key returned fields. It could be improved by clarifying its relationship to get_all_lineups and by noting prediction freshness or limitations.

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 single club parameter is fully documented in the schema with name/slug examples. The description adds a useful constraint that the club should be a 2026/27 Premier League club, but it does not add slug normalization or other format details beyond the schema.

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 uses a specific verb and resource: it gets the RoboKlopp AI predicted Starting 11 and related output for a Premier League club. It clearly states the returned content, though it does not explicitly distinguish this single-club tool from the sibling get_all_lineups.

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 phrase 'for a 2026/27 Premier League club' gives useful scope, but the description does not say when to use this tool instead of get_all_lineups, get_match_preview, or other lineup-adjacent siblings. Usage is therefore implied rather than explicitly guided.

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