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RideDesk Developer Docs

by app.ridedesk

Search the documentation

search_docs
Read-only

Keyword search across all documentation topics. Returns matching sections with excerpts; follow up with get_doc for the full topic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoThe operator's RideDesk domain (e.g. their-workspace.ridedesk.app or a custom domain). Optional — examples use a placeholder without it.
queryYesKeywords, an endpoint path, or a field name (e.g. "quote_ref", "apple pay", "/api/enquiries")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoPresent only when there were no matches.
resultsYesMatching sections, best first. Empty when nothing matched.

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "note": {
+      "description": "Present only when there were no matches.",
+      "type": "string"
+    },
+    "results": {
+      "description": "Matching sections, best first. Empty when nothing matched.",
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "excerpt": {
+            "description": "Up to 600 characters of the matching section",
+            "type": "string"
+          },
+          "heading": {
+            "description": "The section heading the match sits under",
+            "type": "string"
+          },
+          "topic": {
+            "description": "Pass this to get_doc for the full topic",
+            "enum": [
+              "overview",
+              "quote-and-book",
+              "checkout",
+              "endpoints",
+              "widgets",
+              "attribution",
+              "live-chat",
+              "customer-portal",
+              "mcp-connector"
+            ],
+            "type": "string"
+          }
+        },
+        "required": [
+          "topic",
+          "heading",
+          "excerpt"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "results"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark the tool as read-only and non-destructive. The description adds useful behavioral context: it returns partial sections with excerpts rather than full documents, and expects a follow-up call to get_doc for complete content.

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?

Two tight sentences with no wasted words. The core action is front-loaded, followed by the result shape and the recommended next step.

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 simple, read-only, one-required-parameter search tool with an output schema and a named sibling for full retrieval, the description plus schema and annotations give the agent everything needed to select and invoke it correctly.

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 coverage is 100%, so the query and host parameters are already well described in the schema. The description reinforces that the query parameter is a keyword search but does not add new parameter-level detail.

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 ('keyword search') and resource ('all documentation topics'), and clarifies that results are matching sections with excerpts. This clearly distinguishes it from get_doc, which retrieves the full topic.

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 explains the search-then-retrieve workflow by saying to follow up with get_doc for the full topic. It does not explicitly contrast with list_docs or the other siblings, but the intended usage is clear and supported.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool clearly serves a distinct purpose: listing topics, searching docs, retrieving a topic, getting an integration brief, and fetching widget code snippets. There is no overlap; an agent can easily choose the right tool.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: list_docs, search_docs, get_doc, get_integration_brief, get_widget_snippets. The verbs (list, search, get) are standard and predictable.

Tool Count5/5

Five tools is ideal for a documentation server, covering discovery (list, search) and retrieval (get) without excess. Each tool earns its place and the set is well-scoped.

Completeness5/5

The tool surface fully covers the domain: you can discover available topics, search across content, retrieve individual topics, and get specialized artifacts (briefs and snippets). There are no dead ends or missing necessary operations.

Resources