diagnose

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the input files it processes and the categories of issues it looks for. However, it does not state whether the tool is read-only, what its output format is, or whether it may apply any changes, leaving some behavioral ambiguity.

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?

A single sentence with no filler. The verb, scope, files, and analysis targets are all front-loaded and each word contributes to the tool's purpose.

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 parameterless diagnostic tool, the description is reasonably complete: it names the sources and expected findings. Still, it does not describe the return value or output shape, and with no output schema or annotations, an agent has to infer what 'likely culprits' will look like when the call completes.

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 tool has zero parameters and an empty input schema, so there are no parameter semantics to add. The description correctly focuses on behavior rather than parameters, matching the baseline for parameterless tools.

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 uses a specific verb, 'Parse', with concrete resources ('latest.log, debug.log, and recent crash reports') and a clear analytical goal ('missing mods, mixins, and likely culprits'). However, it does not explicitly differentiate from sibling tools like read_log, analyze_mods, or health_check, relying on the operational details to imply distinction.

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 implies when to use the tool: when you need to diagnose crashes or mod issues from logs. It does not explicitly state when not to use it, nor does it mention alternatives such as health_check or analyze_mods, so the guidance is only implicit.

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