lgh_up_dryrun

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

The description goes beyond the annotations by enumerating exactly what the tool reports (git repo status, changed files, LGH registration status, auto-register name, trash-detection results, failure reasons) and states it returns a JSON with dry_run=true. It also reaffirms the no-side-effect guarantee ('nothing is committed, pushed, registered, or written'), matching the readOnly and idempotent hints with no contradiction.

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 efficient: two sentences convey the core purpose, a third gives scoping and alternatives, and a fourth states the return format. No redundant wording; every sentence serves a distinct role.

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?

The description includes all necessary context for an agent to decide when to invoke this tool: what it does, what it outputs, when to use it instead of lgh_up or lgh_diff, and its non-destructive nature. It is self-contained without needing external references.

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 only parameter 'path' is described fully as 'Absolute path to the LOCAL working directory (defaults to current directory)', providing both meaning and default behavior. With 100% schema coverage, the parameter semantics are complete.

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 is a dry-run preview of lgh_up, explicitly names the sibling tool it simulates, and differentiates it from lgh_diff by contrasting the output type. The purpose is unambiguous and specific.

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?

It provides direct guidance on when to use this tool ('Call this before lgh_up whenever you are unsure what a backup would include') and when to use the alternative lgh_diff for patch content instead of a changed-file list. The situational selection is explicit.

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