INDUSS Research Intelligence MCP Server

generate_markdown

Idempotent

Converts structured research reports into GitHub-flavored Markdown, adding a table of contents, per-section confidence and sources, and a consolidated citation list.

Instructions

Renders a structured report (see generate_report's schema) into a GitHub-flavored Markdown document with a table of contents, per-section confidence/sources, and a consolidated citation list.

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": {
      "title": "<title>",
      "sections": "<sections>"
    },
    "name": "generate_markdown"
  }
}

Input Schema

Name	Required	Description	Default
`title`	Yes
`sections`	Yes
`subtitle`	No
`companyName`	No
`generatedAt`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations include idempotentHint=true and readOnlyHint=false, and the description adds context by detailing the output structure (GFM, TOC, confidence/sources, citations). This goes beyond the annotations to explain what the transformation produces.

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?

A single, information-dense sentence conveys purpose, input reference, and output features with no unnecessary words. Front-loaded and easy to parse.

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?

Given the tool's complexity and lack of output schema, the description adequately explains what the tool returns (Markdown with TOC, confidence/sources, citations). It does not mention error behavior or return type, but for a rendering tool this is acceptable. The reference to generate_report's schema anchors the input context.

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 description coverage is 0%, so the description must compensate. It references generate_report's schema, which helps an agent understand the input structure, but it does not explain individual parameters (title, sections, etc.) or how they map to the output. The schema is fairly self-explanatory, but the description could do more.

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 clearly states the tool renders a structured report into GitHub-flavored Markdown, with specific features (TOC, per-section confidence/sources, consolidated citations). It distinguishes from siblings like generate_report (input source) and generate_pdf (different output format).

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 phrase 'see generate_report's schema' strongly implies this tool consumes the output of generate_report, providing clear context for when to use it. However, it does not explicitly mention alternatives like generate_pdf or exclusions, 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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