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 states the tool analyzes results and returns a formatted string, but lacks details on permissions, rate limits, error handling, or whether it modifies data. For a tool with no annotations, this is insufficient to inform safe and effective usage.

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 appropriately sized and front-loaded, with the core purpose stated first, followed by parameter and return value sections. Each sentence adds value, but the structure could be slightly improved by integrating usage context. Overall, it is efficient with minimal waste.

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 the tool's complexity (2 parameters, no annotations, but with an output schema), the description is moderately complete. It explains the purpose and parameters but lacks behavioral details and usage guidelines. The output schema indicates returns are a string, so the description need not elaborate on return values, but overall gaps remain in guiding effective tool selection and invocation.

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 meaning by explaining 'jtl_file' as 'Path to the JTL file containing test results' and 'detailed' as 'Whether to include detailed analysis (default: False)', which clarifies their roles beyond the schema's basic types. However, it does not cover all potential nuances, such as file format requirements or what 'detailed' entails specifically.

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 does not explicitly differentiate it from sibling tools like 'get_performance_insights' or 'identify_performance_bottlenecks', which might have overlapping purposes. This makes it clear but not fully distinct from alternatives.

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 its siblings. It mentions analyzing JMeter results but does not specify scenarios, prerequisites, or exclusions compared to tools like 'generate_visualization' or 'get_performance_insights'. Without such context, users might struggle to select the appropriate tool among similar options.

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