llm_fs_find

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It reveals routing behavior (cheap model for pattern thinking) and execution responsibility (Claude executes commands). This adds valuable context beyond the name and distinguishes it from a simple search. However, it could explicitly state that no files are modified.

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?

The description is very concise: two short paragraphs and a brief Args section. The purpose is stated in the first sentence, followed by internal routing info, then parameter details. Every sentence adds value with no fluff.

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?

Given the tool's moderate complexity, lack of annotations, and presence of an output schema, the description adequately covers purpose, routing, and parameter details. It does not cover error cases or prerequisites, but for a read-style find tool, the completeness is sufficient. No major 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?

Schema description coverage is 0%, requiring the description to compensate. The description provides detailed explanations and concrete examples for both parameters: description ('What you’re looking for, e.g. ...') and root ('Optional root directory to search in. Defaults to current working directory.'). This adds significant meaning beyond the schema's bare titles and types.

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 generates glob/grep commands to find files matching a natural-language description. It uses a specific verb (generate) and resource (commands to find files), and naturally distinguishes from sibling file-system tools like llm_fs_analyze_context, llm_fs_edit_many, and llm_fs_rename which have different purposes.

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 provides clear context: use this tool when you want to find files based on a natural-language description. It does not explicitly mention when not to use it or alternatives, so it misses the top tier of explicit exclusions, but the context is clear and adequate for an AI agent.

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