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opencode-document-rag-mcp

opencode-document-rag-mcp

by humbertolvarona
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_documents

Lists supported documents in the DOCS directory while excluding the mdDB internal folder, giving you a clear view of available files for retrieval.

Instructions

List supported documents under DOCS while excluding DOCS/mdDB.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_documents"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations available, the description carries the full burden of behavioral disclosure. It reveals that the tool is read-only in nature (a list operation) and scopes results to DOCS while excluding DOCS/mdDB, but it does not explicitly state that it causes no side effects or describe other behaviors such as sorting, pagination, or error conditions. The exclusion is useful context, but the description remains thin on overall behavioral cues.

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, tightly packed sentence that immediately states the action, scope, and exclusion. There is no filler, and the most important information (the exclusion) is included without excess. This is an exemplary concise and well-structured description.

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?

The tool is low complexity with no parameters and an existing output schema, so the description does not need to explain return values. The only potential gap is the meaning of 'supported documents,' but for a simple listing tool, this is minimally ambiguous and likely inferable from context or the output schema. Overall, the description is sufficiently complete for an agent to call the tool 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 takes zero parameters, and the schema coverage is 100% (vacuously). Per rubric, a tool with no parameters gets a baseline score of 4 since there are no parameter meanings to clarify; the description correctly avoids irrelevant parameter details.

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 action ('List') and a precise resource scope ('supported documents under DOCS') and adds an explicit exclusion ('excluding DOCS/mdDB'). This clearly differentiates it from sibling tools that ingest, search, or read documents, making the tool's purpose unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives like search_documents or read_markdown_section. It does not mention any context or conditions that would direct the agent away from other tools, leaving the decision entirely to inference from the tool's name and basic purpose.

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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