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LCM2M

lcm2m-caddis-mcp

by LCM2M

List equipment manufacturers

caddis_list_manufacturers
Read-onlyIdempotent

List all equipment manufacturers sorted by name, decode manufacturer details, and retrieve IDs for model lookups.

Instructions

List equipment manufacturers defined for the company, sorted by name. Use to decode the manufacturer of a piece of equipment or to look up a manufacturer ID for caddis_list_models.

Responses are TOON-encoded (toonformat.dev) — a token-efficient JSON dialect mixing YAML-style indentation with CSV-style tables. Example:

name: Caddis Co timezone: America/Denver equipment[3]{id,name,tags,current_status.status,current_status.reason_id}: 1,Mill A,"["cnc","critical"]",running,null 2,"Press, Big",null,down,3 3,Lathe C,null,null,null

  • Object fields: key: value; nested objects indent their children.

  • Uniform arrays of objects: field[N]{cols}: followed by N indented comma-separated rows in column order.

  • Nested objects inside table rows are recursively flattened to dotted columns (e.g. current_status.status, input_setup.cycle.logic); a null parent yields null across all its dotted columns (see row 3 above).

  • Primitive arrays at object level: field[N]: a,b,c inline.

  • Arrays inside table cells are JSON-stringified into a single cell value (JSON.parse() to recover); empty arrays render as null (see rows 1–3 tags column).

  • Strings with commas/colons/quotes/leading whitespace are double-quoted (escapes: \\, \"); other strings, numbers, booleans, and null are bare.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds substantial behavioral details: it explains the TOON-encoded response format with examples, clarifies the sorting behavior, and notes that responses are token-efficient. This goes beyond the annotations and helps the agent handle the output correctly.

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 front-loaded with the core purpose and usage, then provides a detailed but necessary explanation of the TOON format. While the format explanation is long, it is essential for correct interpretation. The structure is logical and each sentence serves a purpose.

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 that there are no parameters and the annotations already cover readOnly, openWorld, and idempotent aspects, the description fully compensates by thoroughly documenting the response format (TOON encoding) with an example. No important aspect is missing for an agent to invoke and interpret the tool correctly.

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?

There are zero parameters, so the description cannot add parameter-level detail beyond the schema (which has 100% coverage by stating no properties). The baseline is 4, and the description does not contradict or improve that; it simply provides contextual meaning for the tool's no-parameter interface.

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 lists manufacturers sorted by name and explicitly says it can be used to decode a manufacturer or look up an ID for caddis_list_models. This establishes a specific verb+resource combination and distinguishes it from sibling list tools that list different entities.

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 description provides explicit use cases ('Use to decode...' and 'look up a manufacturer ID...'), which guides when to use the tool. It does not include when-not-to-use or mention alternatives, but the given context is sufficient for an agent to decide.

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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