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AgentWorld MCP Server

AgentWorld MCP Server

by shawnhvac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_ambiguity_score

Score supplier communication for ambiguity, flag vague phrases and explicit commitments, and return a verdict with rationale to catch "best effort" wording before it causes financial drift.

Instructions

[FREE] Semantic Contract Drift Detector (AgentWorld invention 3857).

Scores natural-language supplier communication for ambiguity (0.0 explicit, 1.0 maximally vague) with flags for vague phrases, explicit commitments found, a verdict (LOW/MODERATE/HIGH) and a rationale. Catch 'best effort' language before it becomes financial drift. Max 8000 chars.

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": {
      "text": "<text>"
    },
    "name": "get_ambiguity_score"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the 0.0-1.0 scoring range, the return contents (vague-phrase flags, explicit commitments, LOW/MODERATE/HIGH verdict, rationale), and an input cap of 8000 chars — a real behavioral constraint. It leaves open whether input is stored or whether any rate limit applies beyond 'FREE', but the core behavior is well covered.

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?

Purpose, scoring scale, return contents, and input limit are all front-loaded in four tight sentences. The '[FREE]' tag and the contract-drift framing are compact and informative; the only real filler is the '(AgentWorld invention 3857)' attribution, which is small relative to the value delivered.

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

Completeness4/5

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

For a one-parameter, annotation-free tool with no output schema, the description supplies the essential missing pieces: output shape, scale interpretation, and input length limit. Only minor gaps remain (input format expectations, whether submitted text is persisted), which do not block correct invocation.

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?

Schema coverage is 0%, so the description must compensate — and it does: it tells the agent the single 'text' parameter should be natural-language supplier communication and that it is capped at 8000 characters. It stops short of specifying expected format (plain text vs. structured) or language handling, but meaning well beyond the bare schema is added.

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?

States a specific verb and resource ('Scores natural-language supplier communication for ambiguity') plus the scale (0.0 explicit to 1.0 maximally vague) and the outputs (flags, verdict, rationale). No sibling tool in the list does ambiguity scoring, so the agent can identify this unambiguously.

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?

The line 'Catch best effort language before it becomes financial drift' implies the use case (reviewing supplier/vendor wording before committing), but there is no explicit 'use when / do not use when' framing and no named alternative. Usage is inferable rather than directed.

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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