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

Annotations already indicate readOnly and non-destructive behavior. The description adds useful model context: logistic model fitted on 8,000+ archived matches, per format and innings, with pre-match Elo, and clarifies the output includes batting-side probability and favored side. This goes beyond what annotations provide.

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 compact and front-loaded with the core purpose, followed by model provenance and concrete use cases. All three sentences contribute value, though the phrasing 'who is favored' and the quoted use cases could be slightly more formal.

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 tool with no output schema, the description adequately states what the caller receives: the batting side's probability and who is favored. With 9 parameters all documented in the schema and annotations covering safety, the description is sufficient for an agent to understand scope and output. Some edge-case behavior around innings and target is left implicit, but the schema fills that gap.

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 the parameters are already fully documented in the schema. The description does not add further parameter-level detail but does clarify that the returned probability applies to the batting side, which is mildly helpful context.

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 clearly states the tool computes win probability for a live or hypothetical limited-overs match state and returns the batting side's probability and favored side. It is specific enough to distinguish from siblings like cricket_live_matches or cricket_match_archive, though it does not explicitly name a sibling alternative.

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 gives explicit use cases: 'who is winning' or 'what are the odds at X/Y'. This provides clear context for when the tool is appropriate, though it does not mention when not to use it or explicitly compare it to alternatives like cricket_market_odds.

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