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publish_draft

Convert a managed revision into a new native Jianying draft and register it on the home page, with optional dry-run validation and no overwrite of existing drafts.

Instructions

Add a managed revision as a NEW native draft and register it on Jianying's home page.

draft_root must be the absolute existing com.lveditor.draft folder with a recognized plaintext root_meta_info.json. Fully quit Jianying first and keep it closed until a real publication finishes. Defaults to no-write validation. Existing drafts are never replaced; the index is backed up. Native edits are not synced back to the managed source. Publishing does not launch the app or export video. Requires native folder write access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
dry_runNo
draft_rootYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.6/5.0
Behavior5/5

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

The description substantially exceeds the annotations by explaining non-obvious behaviors: existing drafts are never replaced, the index is backed up, native edits are not synced back, and the default is no-write validation. This gives an agent a clear safety and side-effect profile beyond the simple read/write/destructive hints.

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?

The description is dense but every sentence carries useful information: purpose, prerequisites, safety guarantees, exclusions, and access requirements. It is efficiently front-loaded with the core action and then provides constraints in a compact block.

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?

The description covers prerequisites, behavioral guarantees, and exclusions, which is strong for a tool with no output schema. It is slightly incomplete regarding what the tool returns on success/failure, but this is not essential for selecting and safely invoking the tool.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates well for draft_root by specifying it must be an absolute existing com.lveditor.draft folder with root_meta_info.json, and for dry_run via 'defaults to no-write validation.' However, the required 'name' parameter is not explained, leaving a small semantic gap.

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 starts with a specific verb and resource: 'Add a managed revision as a NEW native draft and register it on Jianying's home page.' This clearly distinguishes the tool from siblings like create_draft or edit_draft by emphasizing native publication registration rather than generic creation or editing.

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 concrete when-to-use context: prerequisite folders, the need to fully quit Jianying, and keeping it closed until publication finishes. It also states what the tool does not do, such as launching the app or exporting video, but it does not explicitly name alternative sibling tools for those cases.

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