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lcm2m-caddis-mcp

by LCM2M

List status reasons

caddis_list_status_reasons
Read-onlyIdempotent

Retrieve active status reasons to decode downtime classifications in equipment status logs.

Instructions

List active status reasons available for classifying downtime. Use in combination with caddis_get_equipment_statuslogs to decode reason IDs in the log stream.

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 indicate safe read operation; description adds critical context about TOON-encoded response format, essential for correct parsing.

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?

Description is front-loaded with purpose and usage, but the detailed format explanation is lengthy. However, it is necessary and well-structured with examples.

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?

Thoroughly explains the return format with examples and decoding instructions, fully compensating for the lack of an output schema.

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?

No parameters exist, so schema coverage is 100%. Baseline for 0 params is 4; description adds no parameter info but none is needed.

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?

Clearly states the verb 'list' and resource 'active status reasons' with specific purpose of classifying downtime. Distinguishes from sibling list tools by focusing on status reasons.

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 advises combination with caddis_get_equipment_statuslogs to decode reason IDs, providing clear workflow guidance.

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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