Galatic.ai

Regenerate post part

auto_publish_regenerate_part

Regenerate one part of an Auto Publish post in the background (202). part is "video", "voiceOver" (script and audio), "metadata" (title, description, tags), "thumbnail", or "segment" (one scene of a multi-scene post, chosen by 0-based segmentIndex, then re-stitched). instructions (up to 500 characters) steers it; thumbnail ignores them. Only posts in review, approved or failed can be changed (409), and the post goes back to review, so approve it again with auto_publish_update_post. Follow it with auto_publish_list_posts (status generating, then review or failed); its jobId cannot be polled. Video, segment and voice parts spend Galatic.AI credits and take a job slot.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "postId": "<postId>",
      "part": "<part>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "auto_publish_regenerate_part"
  }
}

Input Schema

Name	Required	Description
`part`	Yes	"video", "voiceOver", "metadata", "thumbnail" or "segment".
`postId`	Yes	postId from auto_publish_list_posts.
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`instructions`	No	Up to 500 characters of direction.
`segmentIndex`	No	segment only: 0-based scene index.
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 27, 2026
- addedInput schema / properties / instructions / description
```
Added value: +"Up to 500 characters of direction."
```
- addedInput schema / properties / part / description
```
Added value: +"\"video\", \"voiceOver\", \"metadata\", \"thumbnail\" or \"segment\"."
```
- addedInput schema / properties / postId / description
```
Added value: +"postId from auto_publish_list_posts."
```
- addedInput schema / properties / segmentIndex / description
```
Added value: +"segment only: 0-based scene index."
```
Changed1 schema field changedOct 26, 2026
- changedInput schema / properties / segmentIndex / minimum
```
Previous value: --9007199254740991New value: +0
```
First observedOct 24, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the non-readonly and non-idempotent annotations, the description discloses background 202 behavior, status restrictions, the review-state reset, the inability to poll the returned jobId, and credit/job-slot consumption. These are substantive operational details an agent needs before invoking it.

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?

The definition is dense but front-loaded with the main action and part enumeration, then proceeds to operational constraints. Every sentence is useful, though the paragraph is lengthy for a single description.

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?

For a complex mutation with no output schema, the description covers the necessary status model, asynchronous behavior, follow-up procedure, and cost implications. An agent can invoke it correctly without needing additional external context.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: thumbnail ignores instructions, segment requires segmentIndex and re-stitching, and instructions are capped at 500 characters. It does not separately explain context, llm_model, or conversation_id, but those are fully documented in the schema.

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 names a specific verb and resource: regenerate one part of an Auto Publish post. It enumerates the valid parts and distinguishes the tool from siblings such as auto_publish_update_post and auto_publish_list_posts.

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?

It explicitly states which post statuses permit the call and which return 409, says the post returns to review and must be re-approved, and names the follow-up tool. It also names auto_publish_update_post as the approval alternative.

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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