homebox-mcp

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field_index

Read-only

Scan every entity to build a custom field-to-asset ID index for deduplication before bulk import, preventing duplicate records.

Instructions

Return {field_value: assetId} for every entity that has the named custom field — a one-pass index for DEDUPE before a bulk import (q does not index custom fields, so this scans every entity). field_name defaults to $HOMEBOX_ALIAS_FIELD. assetId may be empty for un-asset'd rows. Deliberately uncapped: a truncated dedupe index causes duplicates, so expect a large result on a large inventory.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "field_index"
  }
}

Input Schema

Name	Required	Description	Default
`field_name`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 2, 2026

TDQS

A5/5.0

Behavior5/5

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

The description goes beyond the readOnlyHint annotation by disclosing that the tool scans every entity (performance implication), returns empty assetId for un-asset'd rows, is deliberately uncapped to prevent duplicates, and may return a large result on large inventories. This is rich behavioral context that annotations alone do not provide.

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?

The description is concise yet information-dense. Every sentence serves a purpose: defining output, use case, parameter default, edge case, and size rationale. No wasted words.

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?

Despite being a simple tool, the description covers the return structure, use case, performance caveats, edge cases (empty assetId), and result size expectations. This is fully adequate for an AI agent to safely invoke the tool.

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?

With 0% schema description coverage, the description fully compensates by explaining the 'field_name' parameter: it is a custom field name and defaults to $HOMEBOX_ALIAS_FIELD. This adds meaning beyond the bare schema fields.

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 opens with a specific action and resource: 'Return {field_value: assetId} for every entity that has the named custom field'. It clearly defines the tool's purpose as building a custom-field index for deduplication before bulk import, distinguishing it from sibling tools like search_items.

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?

Explicitly states when to use the tool: 'for DEDUPE before a bulk import'. Also explains why it is necessary: 'q does not index custom fields, so this scans every entity'. This gives clear context for choosing this tool over alternatives.

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