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Find YouTube API methods, schemas, metrics, and quota costs by running JavaScript; no network, auth, or quota needed.

Instructions

Explore the YouTube API specs by running a JavaScript async function body. No network, no auth, no quota.

A global spec holds:

  • spec.youtube: Data API v3 Discovery doc. Methods live at spec.youtube.resources..methods., with httpMethod, parameters (description, required, repeated, enum), and request/response $ref schemas in spec.youtube.schemas.

  • spec.analytics: YouTube Analytics v2 Discovery doc (reports.query, groups, groupItems).

  • spec.analyticsFields: { metrics, dimensions } with descriptions, since the Analytics Discovery doc does not list them.

  • spec.reporting: YouTube Reporting v1 Discovery doc.

  • spec.quotaCosts: { "youtube.videos.list": { bucket, cost }, ... }.

Return only what you need. Examples: return Object.entries(spec.youtube.resources.videos.methods).map(([k, m]) => ({ k, params: Object.keys(m.parameters ?? {}) })) return spec.youtube.schemas.VideoSnippet.properties return Object.keys(spec.analyticsFields.metrics).filter((m) => /revenue/i.test(m))

Method ids found here map 1:1 to execute(): spec.youtube.resources.videos.methods.list is yt.data.videos.list(params).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesAsync function body. Use return.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: 'No network, no auth, no quota' declares the sandbox constraints, and the global `spec` map tells the agent exactly what data is reachable. It omits error behavior, execution-time limits, and output-size limits, which keeps it from a 5.

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?

Purpose is front-loaded in sentence one, constraints second, and the data map and examples follow in scannable bullets. Despite its length, every block supplies information needed to write a correct function body; there is no filler.

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 complex code-execution tool with no output schema and a single fully-documented parameter, the description covers environment constraints, available globals, return guidance, examples, and the hand-off to execute(). Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already explains `code` as 'Async function body. Use return.' The description goes well beyond that by documenting the global `spec` object, its sub-namespaces, and worked examples of valid function bodies, which is exactly the semantics an agent needs to author the parameter.

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 first sentence names a specific verb (explore), a specific resource (YouTube API specs) and the mechanism (running a JS async function body). It also states the relationship to the sibling execute() ('Method ids found here map 1:1 to execute()'), so an agent can separate discovery from invocation without opening either schema.

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 establishes a clear context (exploration/discovery of specs) and explicitly routes the agent onward to execute() for actual calls, plus three concrete example queries. It does not, however, state when to prefer this over the 'docs' sibling or any when-not condition, so a small inference remains.

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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