Lineup legality and optimization check

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the description does not need to repeat safety. It adds valuable behavioral context by listing the specific detection categories (unfilled slots, byes, OUT/DOUBTFUL, IR violations, bench optimization), which tells the agent what to expect from the audit. It does not describe the return format, but given no output schema, the list of checks partially compensates.

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 paragraph that front-loads the primary purpose and then enumerates specific checks, which is efficient and informative. It is not overly verbose for the complexity of the tool, and each sentence adds value. The final sentence gives usage triggers, which is useful. It could be slightly tighter, but it is well-structured.

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?

Given the tool's complexity (multiple checks), no output schema, and annotations covering safety, the description is quite complete in explaining what the tool does and when to use it. It does not describe the return format, but the enumerated checks give the agent a strong expectation of the output content. For an audit tool, this is largely sufficient, though a note about output structure would make it fully complete.

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 description coverage is 100%, so all four parameters are documented with descriptions (week, year, teamId, leagueId). The description adds no extra meaning beyond the schema — it merely restates that week is required because rosters and byes are week-specific, which is already in the schema's week parameter description. Baseline of 3 is appropriate since the schema carries the semantic load.

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 states a specific verb ('audit') applied to a specific resource ('a team's lineup for a week') against league requirements and player availability, and enumerates the exact checks performed (unfilled slots, byes, OUT/DOUBTFUL, IR issues, bench optimization). This clearly differentiates it from siblings like get_roster (which shows raw data) and get_health (which likely reports player health) — the tool is an analytical audit.

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 description explicitly says to use it for questions like 'is my lineup set', 'am I missing anything', and 'IR or bench optimization questions', giving clear context. However, it does not name alternative tools or state when to use them instead (e.g., when you need raw roster data, use get_roster). The guidance is adequate but not exhaustive.

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