llm_investigate

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

With no annotations, the description carries full burden for behavioral disclosure. It only states the output 'return next-tool hints' but omits side effects, safety (e.g., read-only vs destructive), authorization needs, or whether it modifies state. This is insufficient for safe invocation.

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?

At one sentence, the description is concise, but it sacrifices necessary content. While brevity is valued, it omits critical information, making it minimally viable. It is appropriately sized for a simple tool but inadequate for the given parameter count and sibling complexity.

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?

Although an output schema exists (mitigating the need to describe return values), the description lacks context on parameters, usage scenarios, and behavioral traits. Given the tool's complexity (3 params, 1 required) and many similar siblings, the description is incomplete for an agent to correctly select and invoke it.

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 description does not mention any parameters, and the schema has 0% description coverage. The three parameters (capture_path, focus, limit) are entirely undocumented, providing no semantic value beyond their names. This is a critical gap.

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 'Run a compact investigation recipe set and return next-tool hints' clearly states the action (run a recipe) and the output (hints). It is specific enough to convey the main function, though it does not differentiate from sibling tools like llm_investigate_all.

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 is provided on when to use this tool versus alternatives. The description does not mention prerequisites, context, or scenarios where this tool is preferred, leaving the agent without decision criteria.

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