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publish_batch

Publish or schedule multiple approved posts across YouTube, Facebook, and TikTok in one batch, validating every job first so invalid entries block the entire run.

Instructions

Run several posts: e.g. one video to three platforms at once, or a week of scheduled posts.

Only call this after the user approved every post in the batch. jobs: list of {platform, video, caption, title?, tags?, schedule_at?, options?} (same fields as publish; caption_file may replace caption). All jobs are validated first: if one is invalid nothing runs. Jobs run in parallel tabs (max_parallel), but one job per platform at a time. Returns {ok, results:[...]} in the input order.

Input Schema

NameRequiredDescriptionDefault
jobsYes
dry_runNo
keep_tabNo
max_parallelNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, it discloses important behavior: all jobs are validated first and nothing runs if any job is invalid, jobs run in parallel tabs subject to max_parallel, only one job per platform runs at a time, and results are returned in input order. These details materially help an agent anticipate side effects and execution semantics.

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 compact and front-loaded: it states the operation, approval guard, job shape, validation/execution behavior, and return shape without filler. Every sentence carries useful information.

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?

Given the output schema and annotations, the description covers most of what an agent needs: batch purpose, job fields, atomic validation, parallelism, and return ordering. It still omits dry_run/keep_tab semantics and does not clarify what happens if a job fails after validation.

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?

With 0% schema description coverage, the description partly compensates by documenting the jobs item structure and explaining max_parallel. It leaves dry_run and keep_tab undocumented, so parameter semantics are only partially covered.

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 states a specific verb and resource ('Run several posts') and gives concrete batch examples, clearly distinguishing it from the single-post sibling publish. An agent can immediately tell this is the batch-publishing tool.

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?

It gives a strong usage prerequisite ('Only call this after the user approved every post in the batch') and batch scenarios such as one video to three platforms or a week of scheduled posts. However, it does not explicitly name publish as the alternative for single posts or state when not to batch.

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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