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Sofiamishel2003

Coherence Analysis MCP

by Sofiamishel2003
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_output_schema

Retrieve the JSON schema for analyze_coherence's structured output, so orchestrators know the fields to expect (incoherences, coherence_score, summary, discarded_count) without making a preliminary call.

Instructions

Return the JSON schema of the structured output produced by
analyze_coherence, so the orchestrator knows what fields to expect
(incoherences, coherence_score, summary, discarded_count) without
needing to call the tool first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It clearly indicates a read-only introspection behavior by saying it 'returns' the schema and that the orchestrator does not need to call analyze_coherence first. No side effects or surprising behaviors are implied.

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?

The description is a single focused sentence that front-loads the core purpose, then adds the key benefit and the expected fields. Every part earns its place with no repetition or filler.

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?

For a zero-parameter introspection tool, the description is complete: it states what is returned, the source tool, the expected fields, and the orchestration benefit. No additional details are needed for an agent to call it correctly.

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 has zero parameters, so the description does not need to document parameter behavior. It adds value by listing the exact fields the returned schema will include, which is useful context beyond the empty input schema.

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?

The description states a specific verb ('Return') and a specific resource ('the JSON schema of the structured output produced by analyze_coherence'). It also differentiates this tool from its sibling analyze_coherence by clarifying that it returns metadata rather than the analysis output itself.

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?

The description gives clear context: use this tool to know what fields to expect from analyze_coherence before calling it. It implies the alternative of calling analyze_coherence first and explains why this tool is preferable ('without needing to call the tool first'), though it does not explicitly enumerate when not to use 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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