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lgh_save

Create a local Git checkpoint by committing working directory changes without pushing to any remote. Ensures .gitignore exists, aborts on blocking issues, and reports success or clean tree status.

Instructions

Create a local checkpoint: ensures a .gitignore exists, then git add + git commit in the working directory WITHOUT pushing anywhere — nothing is synced to the LGH server or any other remote. Initializes git if the directory is not a repo yet, and aborts when trash detection finds blocking issues. Use this for intermediate saves; switch to lgh_up when the work should also reach the LGH backup. Returns JSON with success and a human-readable output line ("Nothing to commit, working tree clean" when there are no changes).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoAbsolute path to the LOCAL working directory (defaults to current directory)
messageYesGit commit message

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

The description discloses all behavioral traits beyond annotations: it 'ensures a .gitignore exists', 'Initializes git if the directory is not a repo yet', 'commits locally without pushing', and returns JSON with a human-readable output line. These details are consistent with the annotations (readOnlyHint=false, destructiveHint=false).

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 somewhat verbose (four sentences) but each sentence adds essential information: action, side effects, usage guidance, and return format. It is logically structured and not redundant, meriting a 4.

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 parameters, no output schema, no nested objects), the description is complete: it covers purpose, usage, side effects, and return format. The absence of an output schema is compensated by explicitly describing the return value.

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

Parameters3/5

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

Schema description coverage is 100%: both 'path' and 'message' have clear descriptions. The tool-level description adds no additional parameter-specific details beyond what the schema already provides, so baseline 3 is appropriate.

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

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Create a local checkpoint: ensures a .gitignore exists, then git add + git commit in the working directory WITHOUT pushing anywhere'. It also explicitly differentiates from lgh_up by noting 'switch to lgh_up when the work should also reach the LGH backup', making the resource and scope unambiguous.

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

Usage Guidelines5/5

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

The description provides direct usage guidance: 'Use this for intermediate saves; switch to lgh_up when the work should also reach the LGH backup.' It also mentions when it aborts ('aborts when trash detection finds blocking issues'), giving clear conditions for use.

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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