fix

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

Goes well beyond annotations by explaining that results are evidence from the user's own history, not guaranteed fixes, and that every line of a stack trace is checked. It also discloses the meaning of an empty result, which is essential for correct interpretation.

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?

Every sentence provides unique, necessary information without redundancy. The description is well-organized, front-loading the core action and then adding important caveats and result interpretation.

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 no output schema, the description fully explains what to expect (commands, empty result, non-guarantee), making the tool's behavior complete and self-contained. The complexity is moderate, and the description covers all necessary aspects.

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 describes both parameters (error and limit), but the description adds value by clarifying that entire stack traces are acceptable and that all lines are checked. This enhances the meaning of the error parameter beyond the schema's generic description.

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 returns commands that followed a given error in past sessions, with the specific usage of passing failing output verbatim. It distinguishes itself from sibling tools by focusing on error-to-command history recovery, not generic recall or diagnostics.

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?

It explicitly says to use this tool when hitting an error before diagnosing, and gives clear instructions to pass the failing output verbatim. It does not discuss alternatives or when not to use it, but the context is clear enough to infer appropriate usage.

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