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

No annotations provided, but description discloses output details: individual match records with price at kickoff, fulltime, +1h, +24h and aggregate stats. Adequate for a read-only analytical tool.

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 concise sentences, front-loaded purpose, no 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?

Covers purpose, output fields, and parameter usage via example. No output schema exists, but description sufficiently explains return values.

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%; description does not add parameter-level meaning beyond the schema. Baseline of 3 applies.

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 the tool does 'Historical match-to-price correlation' with a concrete example ('what happens to BAR after Champions League wins?'), clearly distinguishing it from siblings like tokenintel_match_impact_history.

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?

Provides a clear usage example and context ('ask what happens to BAR after wins'), but does not explicitly state when to avoid or mention alternatives.

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