analyze_jmeter_results

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analyzing results and returning a formatted string, but lacks details on permissions, rate limits, error handling, or whether it modifies data. For a tool with no annotation coverage, this is insufficient to inform safe and effective use.

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 well-structured and front-loaded, starting with the core purpose followed by parameter explanations. Every sentence adds value without redundancy, and the formatting with 'Args:' and 'Returns:' sections enhances readability. It's appropriately sized for the tool's complexity.

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 annotations, 0% schema coverage, and an output schema present (which handles return values), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines. For a tool with siblings and potential complexity in performance analysis, it should do more to guide the agent effectively.

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 adds meaningful context: 'jtl_file: Path to the JTL file containing test results' and 'detailed: Whether to include detailed analysis (default: False)'. This clarifies parameter purposes beyond the schema's basic types, though it could elaborate on file format or detailed analysis specifics. With 0% coverage, this is strong but not exhaustive.

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: 'Analyze JMeter test results and provide a summary of key metrics and insights.' It specifies the verb ('analyze') and resource ('JMeter test results'), but doesn't explicitly differentiate from siblings like 'get_performance_insights' or 'identify_performance_bottlenecks', which might offer overlapping functionality. This makes it clear but not fully distinguished.

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 provides no guidance on when to use this tool versus alternatives. With siblings such as 'execute_jmeter_test', 'generate_visualization', 'get_performance_insights', and 'identify_performance_bottlenecks', there's no indication of context, prerequisites, or exclusions. This lack of comparative guidance leaves the agent to guess based on tool names alone.

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