get_player_connections

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

No annotations provided, but the description discloses that results are aggregate counts, not ball-by-ball data, and that not every opponent appears because the set mirrors the head-to-head pair set. This is sufficient behavioral context.

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?

Description is three sentences, front-loading the core purpose. Each sentence adds value: purpose, use cases, and behavioral nuance. No wasted words.

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 no output schema, the description adequately explains return structure (franchise, bowlers, dismissers, canonical URLs, aggregate counts) and scope (mirrors head-to-head set). Context is sufficient for the tool's complexity.

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% (both parameters have descriptions). The description does not add new meaning to the parameters beyond what the schema provides, meeting the baseline for high coverage.

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?

Clearly states it returns a player's graph neighborhood including franchise, most-faced bowlers, and top dismissers, with canonical URLs and aggregate counts. Distinguishes from get_player_h2h by noting that matchup edges mirror that tool's pair set, preventing confusion.

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 concrete example queries ('who are Kohli's toughest bowlers', 'which team does Kohli play for') and clarifies returns are aggregates not ball-by-ball. Implicitly differentiates from get_player_h2h but does not explicitly state when to use one over the other.

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