Skip to main content
Glama

PrePublish - YouTube script QA

Pre-flight a script against YouTube advertiser and monetisation policy

policy_preflight

Check a script before recording for the YouTube policy categories it may touch: which category families are implicated, the consequence family for each, a verdict and flag counts. Each category cites YouTube's own published policy page. Choose this when the user is writing about sensitive subject matter and asks whether it is safe to monetise. The quoted passages and their suggested rewrites are part of the paid audit, so the free result may return counts with locked quotes. It reports risk against published policy text; it is not a monetisation guarantee and does not speak for YouTube.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoThe planned title, if the user has one. Titles are checked too.
scriptYesThe script text as written, at least 200 characters. Below that there is not enough context for a policy read.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description adds useful context beyond the annotations: the free result may return locked quotes, quoted passages and rewrites belong to the paid audit, and the tool is explicitly not a monetisation guarantee. Nothing contradicts the annotations, though side effects are not elaborated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but front-loaded: the first sentence states purpose and outputs, the second gives usage selection, and the rest add necessary caveats about paid/free behaviour and scope. It could slightly tighten the policy-page citation clause, but it is not padded.

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?

Even without an output schema, the description covers the main result elements, the intended use case, the paid/free boundary, and the tool's limitations. It does not spell out an exact response structure, but an agent has enough signal to decide when to call it.

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 schema already documents both title and script, including the 200-character minimum. The description adds only minor extra framing about checking before recording and does not need to compensate for missing schema details.

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 states a specific action ('Check a script before recording') and lists concrete outputs: category families implicated, consequence family, verdict, and flag counts. It also differentiates from the paid audit siblings by describing this as the preflight/free version with locked quotes.

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 gives an explicit selection trigger: choose this when the user discusses sensitive subject matter and asks whether monetisation is safe. It references a paid audit alternative for quoted passages, but it does not explicitly name a sibling tool or provide a clear when-not-to-use condition.

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