_mcp_generate_performance_report

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

With no annotations, the description should disclose behavioral traits like side effects or read-only nature. It only states 'render' which implies output but no details on whether data is modified, auth needs, or rate limits.

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?

Single sentence is efficient but lacks structure for 5 parameters. Could front-load purpose and then list key behaviors or parameter roles.

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 5 parameters (2 required) and an output schema, the description is incomplete. It doesn't explain required project_id, metrics object, optional baseline, eval_dataset, or notes. Output schema exists but not referenced.

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%, and the description adds no parameter explanations. It mentions 'metrics, baseline comparison, and curves' but does not clarify which parameters correspond or their formats.

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 renders a performance report with metrics, baseline comparison, and curves. It distinguishes from siblings like compare_to_baseline and compute_metrics by focusing on rendering rather than computation.

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 on when to use this tool versus alternatives (e.g., compute_metrics, compare_to_baseline). No prerequisites or context provided.

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