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批量上传章节

batch_publish_chapters

Publishes pending chapters from a local manuscript library in chapter order with rate limiting, continues after failed chapters, and returns per-chapter results; confirm=false dry-runs chapter 1 only.

Instructions

从本地文稿库挑「待发布」章节,按章节号顺序限速依次上传;单章失败不中断,返回逐章结果。confirm=false 时只演练第 1 章(填表不提交),避免在后台留下大量草稿。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo最多上传多少章
use_aiNo
book_idNo番茄书 ID(与 novel_id 二选一,优先)
confirmNo是否真正发布,默认 false
headlessNo是否无头运行,默认 false
novel_idNo本地小说 id(用于解析 tomatoBookId)
detectionNo
article_idsNo指定要上传的 article_id 列表(缺省=该小说下所有待发布章节)
interval_secondsNo每章之间间隔秒数,默认 5

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses rate limiting, sequential ordering, fault tolerance (a single failure does not abort the batch), per-chapter results, and the dry-run behavior that avoids leaving stray drafts. It omits permission/auth requirements and the semantics of mode flags like use_ai and detection.

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?

Two compact sentences, with the core batch behavior front-loaded and the dry-run caveat following. Every clause carries information; slightly dense but efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter tool with no annotations and no output schema, the description covers the primary workflow and failure handling but leaves several mode parameters (use_ai, detection, headless) unexplained and says nothing about required authentication or setup prerequisites.

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 78% (near the 80% baseline), so the schema documents most parameters. The description clarifies confirm's dry-run behavior and the chapter ordering, but adds no meaning for limit, use_ai, detection, or headless, which are undocumented or only minimally described in the schema.

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?

The description states a specific verb and resource: selecting pending-publish chapters from the local manuscript library and uploading them in chapter-number order. It is unambiguous what the tool does, though it never names a sibling (e.g. add_chapter_tomato) to differentiate the batch vs single path explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied through the confirm=false dry-run note, which tells the agent how to preview safely, but there is no explicit statement of when to prefer this over add_chapter_tomato or the other publish siblings. Nothing is misleading, but the when-not guidance is left to inference.

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