Skip to main content
Glama

Browse RedM doc paths

browse
Read-only

Enumerate RedM/RDR3 doc paths in a category/namespace. Use to discover what exists before calling get_document or a targeted grep_docs. NOT a content search — use semantic_search for behavior/concept lookups or grep_docs for token lookups. Returns {path, title, chunks}[].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNo
namespaceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / category / enum
      Previous value: -[
      -  "natives",
      -  "vorp",
      -  "rsgcore",
      -  "oxmysql",
      -  "discoveries",
      -  "jo_libs",
      -  "guides",
      -  "learnings"
      -]New value: +[
      +  "natives",
      +  "vorp",
      +  "rsgcore",
      +  "oxmysql",
      +  "discoveries",
      +  "jo_libs",
      +  "cfx",
      +  "guides",
      +  "learnings"
      +]
  2. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description still adds value beyond that by disclosing the return shape ({path, title, chunks}[]) and by stating the negative behavior (not a content search), though it says nothing about result size, pagination, or defaults when both optional params are omitted.

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?

Three tight sentences, zero padding: scope first, routing second, return shape last. Each sentence earns its place.

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?

With no output schema, the description compensates by stating the return structure, and it fully covers routing relative to siblings. It stops short of explaining the effect of omitting both optional parameters (potentially an unbounded enumeration) and any result limits, which are the remaining unknowns for a 2-param discovery tool.

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 carries the burden, and it only references 'category/namespace' as a phrase without explaining what a namespace means, how it relates to category, whether it is a prefix filter, or what happens when both are omitted. The enum values live in the schema, so this is the minimum viable level for a low-coverage 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?

States a specific verb and resource ('Enumerate RedM/RDR3 doc paths in a category/namespace') and immediately sharpens the scope by saying it is not a content search. The agent can distinguish it from get_document, grep_docs, and semantic_search without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit use case ('discover what exists before calling get_document or a targeted grep_docs') plus explicit exclusions, naming the correct sibling for each alternative lookup type (semantic_search for behavior/concept, grep_docs for tokens). This is textbook when/when-not/alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources