get_complexity_metrics

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

No annotations provided, so description must cover behavior. It explains metrics definitions and risk levels, but does not describe output format, side effects, or performance implications. Adequate but not detailed.

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?

Description is compact with clear sections (usage, output, metrics, risk, prerequisite). However, some phrases like 'complexity' are repeated excessively, and the structure could be more streamlined.

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?

Covers tool purpose, example usage, metric definitions, risk levels, and prerequisite. Lacks explanation of return value structure (no output schema) and does not clarify granularity parameter values (e.g., 'method' vs 'file'). Some gaps remain.

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 baseline is 3. The description adds a usage example and metric details, but does not elaborate on granularity or includeDetails beyond schema descriptions. Minimal added value for 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?

The description clearly states the tool gets complexity metrics (cyclomatic, cognitive, LOC). It distinguishes from sibling analysis tools by explicitly naming the metrics and risk levels.

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?

Provides a usage example and prerequisite (load_project must be called first), but does not specify when to use this tool vs alternatives like analyze_file or get_diagnostics. No explicit when-not-to-use guidance.

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