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lgh_up

Backs up a local directory with one command: ensures .gitignore, initializes git if needed, commits, and pushes to the local LGH server (localhost), with safety checks for large files and secrets.

Instructions

One-click backup: ensures a .gitignore exists, then git add + git commit + git push to the LGH local server (localhost, NOT GitHub/GitLab). Auto-registers the repo with LGH and initializes git if needed, so it also works on a fresh directory. Aborts with an error when trash detection finds blocking issues (large files, .env secrets) unless force is set. If ActionD is running, the result includes event_id and triggered_job_ids for the CI jobs spawned by this push; use the ActionD server's dev_cycle_run tool when you need full job tracing. Returns JSON with success, output, project_type, commit, and optional triggered_job_ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoAbsolute path to the LOCAL working directory (defaults to current directory)
forceNoSkip trash detection (large files, .env) and force push
messageYesGit commit message

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

The description discloses the full workflow (git add, commit, push), the auto-init and registration behavior, and the abort-on-trash-detection logic when force is not set. It also notes the return format and CI trigger condition. However, it does not explicitly warn about potential remote overwrite or that pushes modify the remote repository state.

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

Conciseness2/5

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

The description is unnecessarily verbose and repetitive. It restates the same information multiple times (e.g., 'one-click backup', 'auto-registers', 'trash detection') and includes tangential details about ActionD that could be condensed. A shorter version would convey the same meaning more effectively.

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

Completeness4/5

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

The description covers the operation's side effects, error conditions, and return structure (success, output, project_type, commit, triggered_job_ids). It also explains the auto-initialization and registration behavior. It lacks only a note on typical failure modes or environmental prerequisites, but the essential context is present.

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

Parameters4/5

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

All three parameters are documented in the schema with clear descriptions. The tool description adds contextual meaning, particularly for 'force' (skip trash detection) and 'message' (commit message). Since schema coverage is 100%, the description supplements rather than compensates, making this a strong but not maximal score.

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: a one-click backup that runs git add, commit, and push to the LGH local server. It also explicitly distinguishes LGH from GitHub/GitLab, eliminating ambiguity. The verb and resource are specific and immediately understandable.

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

Usage Guidelines2/5

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

The description does not provide guidance on when to use this tool versus alternatives like lgh_up_dryrun or lgh_save. It mentions behavior but not selection criteria. The user is left to infer the appropriate context from the operation itself.

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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