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PrePublish - YouTube script QA

Audit a YouTube script before recording

audit_script

Run Prepublish's full audit on a YouTube script the user has already written. Returns hook, structure and pacing scores, a script-level attention-risk map naming the passages most likely to lose viewers, and a copy-paste rewrite for each flagged passage. Choose this when the user has a finished or near-finished draft and wants to know what is weak before they record. Do not use it to generate a script, to review a published video, or to check grammar. A free result is released by email, so ask the user for an address rather than guessing one. This is a text-only check of an unrecorded script. It maps relative attention risk inside the draft. It does not measure or predict published YouTube retention, and it cannot account for delivery, editing, thumbnail, topic or distribution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoWhere the free result is sent. Required for every anonymous audit — the backend rejects the request without it. Ask the user; never invent it.
audienceNoTarget audience, only if the user said it.
categoryNoVideo category, only if the user said it.
script_textYesThe script text as the user wrote it. Paste it verbatim; do not rewrite, summarise or clean it first.
video_titleYesThe title the user plans to publish under. The audit checks whether the script delivers this promise.
video_duration_secondsNoIntended runtime in seconds, only if the user stated one. Used for pacing; never assumed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Adds meaningful context beyond the annotations: the email-gated free result, the text-only scope of a pre-record check, and a clear boundary on what it does NOT measure (retention, delivery, thumbnail, topic). The readOnlyHint=false is consistent with 'audit' being a computation. Minor deduction because it doesn't state the return shape of the attention-risk map beyond narrative prose.

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?

Front-loads the action and return, then triggers, then exclusions, then the email caveat, then scope limits. Every sentence earns its place with no redundancy or restatement of the name.

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?

Complete for a 6-param no-output-schema audit tool: it covers purpose, return signals, prerequisites (email), and failure-adjacent limits. The only shortfall is absence of any guidance on the audience/category/duration optional params, though the description's restraint is deliberate.

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%, so baseline is 3. The description supplements with behavioral rules — 'paste it verbatim', 'ask the user for an address rather than guessing one' — that add instruction beyond the schema, but does not deepen per-parameter meaning beyond what the schema already provides.

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?

States a specific verb (run full audit) and resource (YouTube script the user has already written), and enumerates what comes back (hook/structure/pacing scores, attention-risk map, rewrites). It explicitly distinguishes itself from siblings: 'Do not use it to generate a script, to review a published video' sets it apart from audit_hook and check_authenticity.

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?

Explicit positive trigger ('finished or near-finished draft... what is weak before they record') plus three explicit exclusions (generate, review published video, check grammar). It also instructs the agent to collect an email rather than guess one, which is a concrete pre-call behavior.

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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