identify_edge_cases

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

With no annotations provided, the description carries the full burden. It describes the tool as analyzing for known edge cases and returning severity, frequency, affected markets, and mitigations, indicating a read-only analytical operation. It does not mention auth, rate limits, or state changes, but the description is sufficient for a safe 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?

The description is relatively concise with two paragraphs, front-loading the purpose. It could be slightly more compact, but every sentence adds value by clarifying examples and output details. 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?

Given that there is an output schema (true) and the schema covers 100% of parameters, the description completes the picture by mentioning the types of edge cases and output attributes. It is adequate for a tool of this 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?

The schema already covers both parameters (sport_type and market_preferences) with descriptions. The description adds value by providing concrete examples for market_preferences ('H2H, props, futures, etc.') and outlining the output attributes (severity, frequency) that relate to the tool's functionality.

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's purpose: 'Identify sport-specific edge cases that affect betting market integrity.' It provides specific examples like race delays, weather disruptions, and disqualifications, making the scope unambiguous. This distinguishes it from siblings like 'detect_trading_anomalies' which focus on different aspects.

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 implies usage for analyzing a sport type for edge cases and optionally filtering by market types. However, it does not provide explicit guidance on when to use this tool over alternatives (e.g., 'detect_trading_anomalies' or 'research_league'). There are no when-not-to-use or exclusion statements.

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