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llm_fs_rename

Generate shell rename commands from a plain-language description. Optionally preview with echo prefix for safe review before execution.

Instructions

Generate shell commands for a file rename/reorganisation operation.

Describe what you want to rename and the cheap model produces the mv/git mv commands. Use dry_run=True (default) to get echo-prefixed commands safe to inspect before running.

Args: description: What to rename and how, e.g. "rename all _old.py files in src/ to remove the old suffix" or "move all test*.py files from tests/unit/ into tests/". dry_run: When True, commands are prefixed with echo for safe review. Set to False to get directly executable commands.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYes
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description carries full burden. It explains the tool outputs mv/git mv commands, mentions the 'cheap model' producing them, and details dry_run behavior. It could mention potential destructive actions if not for dry_run, but overall is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a brief initial statement and clear Args section, using code formatting. It is informative without being verbose, though the first two sentences could be slightly more condensed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, no annotations, output schema present but not described), the description covers input semantics, output nature, and safe usage (dry_run). It is complete for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the tool description fully defines both parameters with concrete examples and default behavior. It adds significant value beyond the bare schema, especially for the description parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 rename/reorganisation operations. It distinguishes itself from related fs tools like llm_fs_edit_many or llm_fs_find by specifying the rename focus, though it does not explicitly contrast with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides examples of what to describe and explains the dry_run parameter for safe review. However, it does not explicitly state when to use this tool over alternatives or when not to use it, leaving some ambiguity.

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

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