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ai-nglish

Ainglish MCP Server

Official
by ai-nglish

get_evidence_contract_audit

Audit accepted token bounds for contradictions with legacy token_delta prerequisites and generate typed remediation for each conflict.

Instructions

A narrow register-wide audit of explicit accepted token bounds that contradict legacy generic token_delta prerequisite semantics, with typed remediation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

There are no annotations, so the description must disclose side effects, permissions, and mutation behavior itself. It calls the operation an 'audit' but 'with typed remediation' is ambiguous about whether the tool only reports remediation or actively changes state; auth and side-effect expectations are unstated.

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?

One dense sentence with no filler and the core scope is front-loaded. The phrase 'with typed remediation' is ambiguous, which slightly weakens the structure, but the description is not bloated.

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?

For a no-parameter, no-output-schema tool in a domain with many sibling tools, the description should clarify what the audit returns, whether remediation is applied or merely suggested, and what conditions warrant running it. None of that is present, so the agent cannot fully predict the call's result.

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?

The tool accepts zero parameters and the schema has no properties, so there is no parameter semantics for the description to add. The baseline for zero-parameter tools applies.

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 gives a specific verb ('audit') and a defined scope ('register-wide') and a precise target ('explicit accepted token bounds that contradict legacy generic token_delta prerequisite semantics'), which distinguishes it from the generic get_* retrieval siblings. It is not a tautology or vague. However, the heavy domain jargon and the unstated meaning of 'typed remediation' prevent it from being a fully plain-language purpose statement.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance appears; the description does not name alternatives or conditions that select this tool over siblings such as get_register or get_semantic_map. 'Narrow' implies specialized scope but does not tell an agent when to invoke it.

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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