download_ai_code_commits_csv

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

No annotations are provided, so the description carries full burden. It discloses the main behavior (download CSV as text) and parameters, but lacks details on error handling, rate limits, or side effects. The GET method implies read-only but is not stated.

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 extremely concise, with only three lines of meaningful content. It front-loads the purpose and lists parameters without redundancy. Every sentence is necessary.

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 has an output schema and only three optional parameters, the description covers the essentials: purpose, return format (csv_text), and filter options. It could mention that the CSV is returned as a string, but the output schema likely provides structure, so it's nearly complete.

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 add meaning. It provides brief explanations for each parameter (e.g., 'Optional start date bound') but lacks format specifications (e.g., ISO 8601) or behavioral details like inclusivity.

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 specifies the tool downloads an AI commit metrics CSV via a GET endpoint and returns the CSV body as text. It uses a specific verb 'download' and resource 'AI commit metrics CSV', distinguishing it from siblings like list_ai_code_commits.

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 lists optional filters but provides no guidance on when to use this tool versus siblings like download_ai_code_changes_csv or list_ai_code_commits. Usage context is implied but not explicit.

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