find_similar_cases

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

With no annotations, the description carries the full burden and does disclose meaningful traits: the content is a curated public library and the figures are explicitly 'second-hand,' a genuine reliability caveat. It also exposes ranking behavior ('a match in the same industry ranks higher'). It omits auth/scope behavior and how csv_path is consumed, so it is strong but not complete.

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 purpose is front-loaded and promising, but the body is fragmented: a provenance note, a bulleted output-handling list, and a dangling 'industry:' parameter note are stitched together with awkward flow. The parts mostly earn their place, but the structure scatters rather than organizes the key facts.

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 3-parameter, 0%-coverage tool with no annotations and no output schema, the description covers provenance, presentation, and the industry parameter but omits the meaning of csv_path and value_event. It is adequate but leaves real gaps an agent must guess at.

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 0%, so the description must compensate. It usefully documents the industry enum values and the ranking rule, but leaves both csv_path and value_event — the two required parameters — unexplained, covering only one of three parameters.

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?

States a specific verb and resource ('Find companies that hit the same problem and what they changed') and frames itself as a 'small library curated from public material.' An agent understands it retrieves analogous case studies. It does not explicitly distinguish itself from siblings like find_aha_moments or compare_benchmark, so it stops short of a 5.

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 detailed instructions for what to do 'when you pass a case on' (explain matched_on, cite the source, offer to apply the fix), which is implicit usage/presentation guidance. However, it never says when to reach for this tool versus find_aha_moments or compare_benchmark, nor any prerequisites, leaving the agent to infer the trigger.

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