analyze_test_cases_duplicates

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

With no annotations provided, the description carries full burden but provides minimal behavioral context. It mentions grouping by step similarity with a threshold range (80-90%), but doesn't disclose what the analysis returns, whether it's read-only or modifies data, performance characteristics, or authentication requirements. The description adds some value but leaves significant gaps.

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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes the key constraint (similarity threshold range) in parentheses. Every word earns its place.

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 7-parameter analysis tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the analysis returns, how results are structured, whether it's a read operation, or any behavioral constraints. The description should do more to compensate for the lack of structured metadata.

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 fully documents all 7 parameters. The description mentions 'step similarity (80-90%)' which aligns with the 'similarity_threshold' parameter's default range, but doesn't add meaningful semantics beyond what the schema already provides. 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 verb ('analyze'), resource ('test cases'), and specific purpose ('for duplicates and group similar ones by step similarity (80-90%)'). It distinguishes from siblings like 'analyze_test_cases_duplicates_semantic' by specifying step-based similarity rather than semantic analysis.

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 duplicate detection with step similarity, but doesn't explicitly state when to use this tool versus alternatives like 'analyze_test_cases_duplicates_semantic' or 'aggregate_test_cases_by_feature'. No exclusions or prerequisites are mentioned.

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