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

Name	Required	Description	Default
`title`	No	The planned title, if the user has one. Titles are checked too.
`script`	Yes	The script text as written, at least 200 characters. Below that there is not enough context for a policy read.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	Yes	Says which parts of the result are paid-only, so a locked field is not read as a clean pass.
`notice`	Yes	The scope limit that accompanies every Prepublish result. Repeat it to the user rather than dropping it.
`policy_preflight`	Yes	The policy read on this script.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "note": {
+      "description": "Says which parts of the result are paid-only, so a locked field is not read as a clean pass.",
+      "type": "string"
+    },
+    "notice": {
+      "description": "The scope limit that accompanies every Prepublish result. Repeat it to the user rather than dropping it.",
+      "type": "string"
+    },
+    "policy_preflight": {
+      "description": "The policy read on this script.",
+      "properties": {
+        "cached": {
+          "description": "True when this exact script and title had already been checked and the stored result was replayed.",
+          "type": "boolean"
+        },
+        "created_at": {
+          "description": "When the pre-flight was produced.",
+          "type": "string"
+        },
+        "preflight": {
+          "description": "The result itself: a verdict of \"no_matches\", \"review_suggested\" or \"high_matches\", the flags, counts_by_category, total_flags, whether the passages are locked, the rubric version it was scored against, the full category rubric with its citations, and the scope statement that must be shown with it.",
+          "type": "object"
+        },
+        "preflight_id": {
+          "description": "Prepublish id for this pre-flight.",
+          "type": "string"
+        },
+        "title": {
+          "description": "The title that was checked, when one was supplied.",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "required": [
+    "notice",
+    "policy_preflight",
+    "note"
+  ],
+  "type": "object"
+}

First observedSep 10, 2026

TDQS

A4/5.0

Behavior4/5

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

Adds real behavioral context beyond the annotations: the free result may return counts with locked quotes because 'quoted passages and their suggested rewrites are part of the paid audit,' and it explicitly disclaims being a monetisation guarantee or speaking for YouTube. Annotations (destructiveHint=false, openWorldHint=false) do not cover this gating or scope limitation, so the disclosure is genuinely additive.

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?

Four sentences, front-loaded with the purpose and output shape before moving to selection guidance and caveats. Every sentence carries load (what it returns, when to pick it, what is locked, what it disclaims), though the phrasing is slightly dense.

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?

With an output schema present the description need not explain return values, and it still covers scope, selection context, paid/free gating, and an explicit liability boundary. Nothing an agent needs to invoke it correctly is missing; the 200-char rule lives in the schema.

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 description coverage is 100%: the schema already documents title (checked too) and the 200-character minimum rationale for script. The description adds no syntax, precedence, or format detail for either parameter, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('check a script... for the YouTube policy categories it may touch') and enumerates what the result contains: category families, consequence family, verdict, flag counts. It is clear what the tool does, though it never contrasts itself with the similarly named sibling audit_script, so an agent must infer the split.

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?

Gives an explicit triggering context: 'Choose this when the user is writing about sensitive subject matter and asks whether it is safe to monetise.' That is a concrete when-to-use condition, but it names no alternatives or exclusions (e.g. when to prefer audit_script or script_runtime instead).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All PrePublish - YouTube script QA tools Inspect

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