ruff_format

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

With no annotations, the description bears full responsibility for disclosure. It states 'Format Python code' but does not clarify that files are modified in-place, whether changes are reversible, or if any safety checks are performed. The agent lacks critical behavioral context for a mutation operation.

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 with no redundancy. Extremely concise and front-loaded, every word earns its place.

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?

Despite having 4 parameters and no output schema, the description does not explain return values (e.g., what is output after formatting?), side effects (file modification), or error behavior. This is insufficient for a tool that modifies files, especially without annotations to fill gaps.

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?

The input schema already covers all parameters (100% coverage). The description adds minimal value beyond the schema, such as explaining the auto-discovery behavior for config_path. For line_length and check_only, the description essentially repeats schema documentation. Overall, marginal enrichment.

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 formats Python code using Ruff. The verb 'Format' and resource 'Python code' are specific, and it distinguishes from sibling tools like ruff_check and ruff_fix by focusing on formatting, though it could explicitly mention that it applies code style.

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 like ruff_check or ruff_fix. There is no mention of typical use cases, prerequisites, or scenarios where formatting is appropriate.

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