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stone_api_search

Search the CAREL System library API for functions and function blocks by keyword, helping AI agents find relevant automation APIs without opening the IDE.

Instructions

Search the CAREL System.* library API (1000+ entries) for functions and function blocks, e.g. keyword 'log', 'alarm', 'modbus'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
keywordNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full disclosure burden, yet it says nothing about result shape, ordering, pagination behavior, default result count, or whether matching is substring or exact. The only behavioral hint is the '1000+ entries' scale, which weakly implies results may be truncated.

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?

A single front-loaded sentence with the verb and resource first and the concrete examples trailing; nothing is wasted. The stray '*' and parenthetical slightly interrupt readability but do not obscure the point.

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

Completeness2/5

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

There is no output schema and no annotations, so the description is the only place an agent could learn what comes back and how 'limit' behaves, and it covers neither. For a search tool intended to feed subsequent code-generation steps, this leaves significant gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, and it only illustrates the 'keyword' parameter through examples ('log', 'alarm', 'modbus'). The 'limit' parameter is never mentioned, leaving its default and effect on results undocumented.

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?

The description names a specific verb (search) and resource (CAREL System.* library API of functions and function blocks) and gives the scale (1000+ entries). It is clear what the tool returns conceptually, though it doesn't state why an agent would pick it over the similarly named sibling stone_symbols.

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

Usage Guidelines3/5

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

Sample keywords ('log', 'alarm', 'modbus') imply the intended usage pattern, so the agent can infer that free-text topical queries are expected. However, there is no explicit when-to-use vs. when-not-to-use guidance and no mention of sibling tools such as stone_symbols or stone_snippet that might overlap.

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