llm_fs_rename

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

With no annotations, the description covers key behaviors: generates mv/git mv commands, uses a cheap model, and dry_run prefixes with echo. This informs the agent of safety and execution mode.

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 well-structured: a concise introductory sentence followed by clear parameter documentation. Every sentence adds value without redundancy.

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 has only 2 parameters and no annotations, the description covers usage and behavior adequately. However, since an output schema exists but is not detailed in the description, the agent might need additional info on return type, but it's still sufficient for invocation.

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 0%, but the description fully explains both parameters: description as a natural language string for rename intent, and dry_run as a boolean controlling command prefix. This adds essential meaning beyond schema 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 shell commands for file rename/organization, with specific examples. It distinguishes from siblings like llm_fs_find or llm_fs_edit_many by focusing on rename operations.

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 explains to describe the rename and notes dry_run default for safety. While it does not explicitly exclude other tools, it provides clear usage context for when to use this tool.

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