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homebutler

homebutler

by Higangssh
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Hybrid

watch_add

Add a Docker container, systemd unit, or PM2 app to the watch list so a separately installed supervisor can monitor it. Duplicate targets return added=false.

Instructions

Add a Docker container, systemd unit, or PM2 app to the watch list. This writes the list and nothing begins watching it — a supervisor has to be installed separately, which only the operator can do. Adding a target twice is reported as added=false rather than an error

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "container": "<container>"
    },
    "name": "watch_add"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindNoWhat it is: docker, systemd, or pm2 (default docker)
unitNoActual unit or app name when it differs from the name above (optional)
serverNoRemote server name from config (optional, runs locally if omitted)
containerYesContainer, unit, or app name to watch

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.31.0

TDQS

A4.3/5.0
Behavior5/5

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

Goes well beyond readOnlyHint=false/destructiveHint=false by disclosing that the write is list-only with no side effect on monitoring, that supervisor installation is out of scope, and that duplicate adds return added=false rather than erroring. These are exactly the behavioral facts an agent cannot infer from annotations.

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

Conciseness5/5

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

Three sentences, each doing distinct work: what it does, what it does not do, and the duplicate-add semantics. Front-loaded with the action, no filler.

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?

No output schema exists, yet the description explains the meaningful return outcome (added=false). For a simple list-mutation tool with full param coverage and declared safety hints, nothing an agent needs is missing.

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%, so kind, unit, server, and container are already documented. The description restates that container/unit/app are the same slot but adds no syntax, format, or default detail for server or unit beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource — 'Add a Docker container, systemd unit, or PM2 app to the watch list' — which immediately separates it from watch_remove, watch_list, and watch_history. It does not explicitly name a sibling alternative, so it falls just short of the top mark.

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

Usage Guidelines4/5

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

The line 'nothing begins watching it — a supervisor has to be installed separately' sets a clear expectation for when this tool alone is sufficient and when install_list or doctor is needed. No explicit instruction to prefer a named sibling, but the context is unambiguous.

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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