analyze_performance

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

With no annotations, the description must carry the full burden of behavioral disclosure. It only states a high-level 'analyze' intent and does not disclose whether the operation is read-only, whether files are modified, what side effects occur, or how results are presented.

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 no fluff. It is appropriately front-loaded with the core action, though it may be overly sparse rather than concise by choice.

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 tool with no output schema and no annotations, the description leaves out essential context such as expected output, side effects, and selection criteria. It is not complete enough for an agent to invoke confidently without more hints.

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 coverage is 100%, so the baseline is 3. The description adds no specific parameter detail, but the schema already documents path, threshold, and includeTests, so no gap exists.

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 function: analyzing code performance and identifying bottlenecks. The verb and resource are specific, and the focus on performance/bottlenecks distinguishes it from sibling tools like analyze_complexity and optimize_memory, though it does so implicitly rather than via explicit naming.

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?

No guidance is given on when to use this tool versus the seven siblings. There is no mention of scenarios, exclusions, or alternative tools, leaving the agent without context to choose between analyze_performance and e.g., optimize_hot_paths or analyze_complexity.

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