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Vee3

by io.github.Vee3io

youtube.search_autocomplete

Get YouTube search autocomplete suggestions for a partial query.

Returns the normalized query and an array of suggested search phrases. Optional language and location codes localize suggestions (defaults: en, US).

Cost = 8 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPartial search keywords or phrase.
languageNoLanguage code for localized suggestions (for example en).en
locationNoCountry code for localized suggestions (for example US).US

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoNormalized query echoed from the provider.
resultsNoSuggested search phrases for the query.

Schema Changelog

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

  1. Changed2 schema fields changed
    • removedOutput schema / $defs
      Removed value: -{
-  "YoutubeSearchAutocompleteResponseResultsItem": {
-    "additionalProperties": true,
-    "properties": {
-      "suggestion": {
-        "anyOf": [
-          {
-            "type": "string"
-          },
-          {
-            "type": "null"
-          }
-        ],
-        "default": null,
-        "description": "Single autocomplete suggestion.",
-        "title": "Suggestion"
-      }
-    },
-    "title": "YoutubeSearchAutocompleteResponseResultsItem",
-    "type": "object"
-  }
-}
    • changedOutput schema / properties / results / anyOf
      Previous value: -[
-  {
-    "items": {
-      "$ref": "#/$defs/YoutubeSearchAutocompleteResponseResultsItem"
-    },
-    "type": "array"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "items": {
+      "type": "string"
+    },
+    "type": "array"
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observed

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral transparency burden. It disclosed the return format (normalized query, array of suggestions), localization defaults, and token cost, which is useful. However, it does not mention rate limits, error handling, or explicitly confirm read-only behavior, leaving some gaps.

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 extremely concise at three sentences. It front-loads the main purpose, then covers return value, localization, and cost without any waste or redundancy. Every sentence earns its place.

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 an output schema, the description is complete. It covers what the tool does, return structure, parameter behavior, and cost. No critical operational details are missing for an agent to invoke it 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?

Schema coverage is 100%, so the baseline is 3. The description adds extra meaning by explaining that language and location localize suggestions and providing their defaults (en, US), which enriches the parameter understanding beyond the schema's individual descriptions.

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?

Purpose is crystal clear: 'Get YouTube search autocomplete suggestions for a partial query.' The verb 'Get' is specific, the resource is clearly YouTube search autocomplete, and the scope is partial queries, distinguishing it from the more general youtube.search sibling.

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

Usage Guidelines3/5

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

The description implies usage for partial queries (e.g., 'for a partial query') but does not explicitly state when to prefer this tool over youtube.search or any other alternative. No exclusions or alternative references are provided, leaving the usage context implicit rather than explicit.

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

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.

Resources