case_study

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

No annotations are provided, so the description carries full burden. It describes what the tool does but lacks behavioral details: no information about permissions needed, rate limits, response format, whether it's a read-only or mutating operation, or how results are returned. For a tool with 3 parameters and no annotation coverage, this is a significant gap in behavioral disclosure.

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?

Well-structured with clear sections: purpose statement, examples of cases, and use cases. Every sentence earns its place by providing value. Could be slightly more concise by combining some bullet points, but overall efficient and front-loaded with the core purpose.

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 3 parameters with 100% schema coverage but no annotations and no output schema, the description provides good purpose and usage context but lacks behavioral transparency. It adequately covers what the tool does and when to use it, but doesn't address how it behaves, what it returns, or implementation details. For a tool with no output schema, some indication of return format would be helpful.

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 schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'match against case studies' which aligns with the 'situation' parameter, but provides no additional syntax, format, or usage details for parameters. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Find and explore Christensen's canonical case studies' with specific examples listed. It distinguishes from siblings by focusing on case studies rather than decision analysis or frameworks, though it doesn't explicitly name the sibling tools. The verb+resource combination is clear but could be more specific about the action (find/explore vs. analyze).

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 'Use this to:' section provides clear context for when to use this tool: finding patterns matching current situations, deep-diving into specific cases, learning lessons, and getting diagnostic questions. It doesn't explicitly mention when NOT to use it or name alternative tools (like analyze_decision or get_framework), but the use cases are well-defined and practical.

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