PrePublish - YouTube script QA

Collect a Prepublish audit by id

get_audit

Read-only

Fetch the current state of an audit that was started earlier, using the analysis_id that audit_script returned. Use this when a previous audit was still running, or when the user refers back to an audit from earlier in the conversation. It performs no new analysis and costs nothing. 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

Name	Required	Description	Default
`analysis_id`	Yes	The analysis_id returned by audit_script.

Output Schema

TableJSON Schema

Name	Required	Description
`notice`	Yes	The scope limit that accompanies every Prepublish result. Repeat it to the user rather than dropping it.
`analysis`	No	The audit at whatever state it has reached: read its "status" field first, because an audit that has not settled carries no scores. Once settled it carries the projected report described on audit_script, and an audit that failed carries its error_message.
`analysis_id`	Yes	The id that was requested, echoed back.
`open_in_browser`	Yes	Permalink to the same audit on prepublish.ai.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 27, 2026

changedOutput schema / properties / analysis / description

Previous value: -"The audit as Prepublish returned it, at whatever state it has reached. Read its \"status\" field: an audit that is not yet settled has no scores."New value: +"The audit at whatever state it has reached: read its \"status\" field first, because an audit that has not settled carries no scores. Once settled it carries the projected report described on audit_script, and an audit that failed carries its error_message."

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "analysis": {
+      "description": "The audit as Prepublish returned it, at whatever state it has reached. Read its \"status\" field: an audit that is not yet settled has no scores.",
+      "type": "object"
+    },
+    "analysis_id": {
+      "description": "The id that was requested, echoed back.",
+      "type": "string"
+    },
+    "notice": {
+      "description": "The scope limit that accompanies every Prepublish result. Repeat it to the user rather than dropping it.",
+      "type": "string"
+    },
+    "open_in_browser": {
+      "description": "Permalink to the same audit on prepublish.ai.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "notice",
+    "analysis_id",
+    "open_in_browser"
+  ],
+  "type": "object"
+}

First observedSep 10, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnly/non-destructive/non-openWorld, and the description adds substantial context beyond them: no new analysis is performed, no cost is incurred, and it explicitly enumerates non-goals (no published retention measurement, no delivery/editing/thumbnail/topic/distribution accounting). This is unusually rich scoping for a read tool.

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?

Front-loaded with the action and the identity key, and every sentence carries routing or scope information. The final negatives list is a bit dense but serves a real disambiguation purpose rather than padding.

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?

An output schema exists, so return structure needn't be described. Combined with the annotation safety profile and the explicit non-goals, an agent has everything needed to call this correctly and to know when not to.

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% and the single parameter is already documented as 'The analysis_id returned by audit_script.' The description restates the same provenance without adding format, validity, or lifecycle detail, so baseline 3 applies.

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 and resource ('Fetch the current state of an audit') and pins the identity key to 'analysis_id that audit_script returned'. This clearly distinguishes it from the sibling audit_script, which produces the audit, and audit_hook.

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?

Gives explicit triggers: 'when a previous audit was still running' or 'when the user refers back to an audit from earlier in the conversation'. It also clarifies cost behavior ('performs no new analysis and costs nothing'), which steers the agent away from re-running audit_script.

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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