costwright_check

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

With no annotations, the description carries full burden. It discloses that the tool builds a .py-only archive, performs static analysis, and returns a summary with counts and verdict. Some details like file size limits or performance are missing, but the key behaviors are transparent.

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?

Two sentences cover purpose, operation, and usage context with no fluff. Front-loaded with the core action ('Statically analyze') and efficient.

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 two simple parameters, the description provides sufficient context: output includes categorized counts and a verdict. Could be slightly more explicit about output format, but overall 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 coverage is 100%, so both parameters have descriptions. The description does not add additional semantics beyond the schema, but the baseline of 3 is appropriate since it doesn't contradict or confuse.

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 purpose: static analysis of LLM-agent repos for runaway-budget risk, specifying supported frameworks and output summary categories. This differentiates well from siblings (certify, pubkey, verify).

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?

Explicitly states when to use ('before deploying a workflow') and that it runs without executing code. However, no explicit when-not-to-use or alternative tools are mentioned, so it loses a point.

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