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mcp-laya

mcp-laya

by dockndevai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

triage

Run preset decision sets over input states to classify urgency, department, sentiment, safety, or policy gates, returning all answers with calibrated confidence.

Instructions

Run a ready-made set of decisions over a state using a laya preset.

presets: triage (department/urgency/sentiment…), email, moderation (safety categories), guard (prompt-injection / policy gates). Returns all answers with confidence.

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": {
      "state": "<state>"
    },
    "name": "triage"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNo
stateYes
presetNotriage

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Because annotations are absent, the description carries the full burden. It does disclose the key behavior—running preset decision sets and 'returns all answers with confidence'—which clarifies output style. It does not mention side effects, authorization, or model execution, so it is only partially transparent.

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?

Two dense sentences with no filler: the first states the operation and the second packs preset guidance plus output expectations into a compact list. Information is front-loaded and scannable.

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

Completeness3/5

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

The definition is adequate for a simple preset-driven tool, especially since an output schema exists and the return value ('all answers with confidence') is mentioned. It falls short on explaining the 'model' parameter, the meaning of 'laya', and when to choose this over sibling tools like decide/classify/score.

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 coverage is 0%, so the description must compensate. It adds real semantics for 'preset' by listing valid values and for 'state' as the analyzed input. However, the optional 'model' parameter is never explained, and 'state' structure is left vague.

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 uses a clear verb–resource pair: 'Run a ready-made set of decisions over a state' and then enumerates presets. This is not a tautology and is distinct from a single classification call, though it never names the sibling tools explicitly, so it stops short of full differentiation.

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?

It provides concrete usage context by listing preset names and their domains (triage for department/urgency/sentiment, moderation for safety categories, guard for prompt-injection/policy gates). There are no exclusions or explicit alternatives, so it misses the top score.

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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