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Glama

Devdocs Io

by io.github.pipeworx-io

Search Docs

search_docs
Read-onlyIdempotent

Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSubstring of a documentation-set name, e.g. "javascript", "postgres".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of items returned.
itemsYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / query / description
      Added value: +"Substring of a documentation-set name, e.g. \"javascript\", \"postgres\"."
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "javascript"
+  },
+  {
+    "query": "react hooks"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of items returned.",
+      "type": "integer"
+    },
+    "items": {
+      "items": {
+        "properties": {
+          "name": {
+            "description": "Display name of the documentation",
+            "type": "string"
+          },
+          "release": {
+            "description": "Release version if applicable",
+            "type": "string"
+          },
+          "slug": {
+            "description": "URL slug identifier for the documentation",
+            "type": "string"
+          },
+          "type": {
+            "description": "Type category of the documentation",
+            "type": "string"
+          },
+          "version": {
+            "description": "Version number if applicable",
+            "type": "string"
+          }
+        },
+        "required": [
+          "name",
+          "slug",
+          "type"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "items",
+    "count"
+  ],
+  "type": "object"
+}
  3. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, but the description adds valuable context beyond annotations: it returns doc SETS, not content, and clarifies the exact boundary of lookup. This behavior is not redundant with the annotations and helps the agent anticipate the tool's output scope.

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 two sentences, front-loaded with the core purpose, includes an illustrative example, and an explicit alternative. Every phrase earns its place; there is no fluff or repetition of schema details.

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 tool with one parameter and an output schema, the description fully covers what the tool does, its limitations, and the alternative path. It is complete for an agent to select and invoke the tool correctly, especially given the annotations and output schema boundary.

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 schema covers 100% of the parameter (query) with its own description, but the description supplements it with concrete examples ('python' → Python 3.x) and explicitly states that the match is a substring of the doc-set name. This reinforces the expected input format and meaning beyond the schema description.

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 finds documentation SETS whose name matches a substring, and explicitly contrasts with search_index to avoid confusion. It uses a specific verb ('find'), resource ('documentation sets'), and scope ('name matches a substring'), making the 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 Guidelines5/5

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

The description explicitly states when to use this tool (to locate doc sets by name) and when NOT to use it ('does NOT look up a function/method/API name'), and names the alternative tool: 'use search_index (slug + query)'. This provides direct usage guidance and disambiguates sibling tools.

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

B3.1/5.0
Disambiguation3/5

There are many tools with overlapping purposes (e.g., multiple ways to ask questions, multiple Polymarket analysis tools, multiple company lookup tools). The detailed descriptions help distinguish them, but an agent could still easily select the wrong one.

Naming Consistency2/5

Tool names are inconsistent, mixing verb_noun patterns (ask_pipeworx, search_docs) with single words (db, docs) and compound names (polymarket_arbitrage, ai_visibility_check). No clear convention across the set.

Tool Count2/5

37 tools is excessive for a DevDocs documentation server; most tools are unrelated to documentation (Pipeworx data, memory, subscriptions). The core documentation functionality only requires about 7-8 tools, making the rest feel extraneous.

Completeness3/5

For the core DevDocs functionality, the tools cover listing, searching, and fetching documentation. However, the server includes many unrelated tools that are incomplete on their own (e.g., only some data lookups, no CRUD for prediction markets). Thus overall completeness is mediocre.

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