Galatic.ai

Episode social copy

episode_social_copy

Draft ready-to-post captions for one episode: youtube (title, description, tags), tiktok, instagram, facebook, x and pinterest, each with a postingTip. Saves them on the episode, replacing any earlier copy, and returns { episode, socialCopy }. Posts nothing. Spends Galatic.AI credits (checked against the remaining budget first; refused with 402 when short). The prompt is written for a kids' animated show. videoAnalysis is optional; without it the captions come from the episode title and cast only. seriesId is the flowId of the Flow Studio flow that holds the series (from list_flows).

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": {
      "seriesId": "<seriesId>",
      "episodeId": "<episodeId>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "episode_social_copy"
  }
}

Input Schema

Name	Required	Description
`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."
`seriesId`	Yes
`episodeId`	Yes
`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.
`videoAnalysis`	No	Optional video analysis of the episode ({ summary, tags, scenes, highlights, transcription }) to ground the captions.
`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.

Changed1 schema field changedOct 26, 2026

addedInput schema / properties / videoAnalysis / description

Added value: +"Optional video analysis of the episode ({ summary, tags, scenes, highlights, transcription }) to ground the captions."

First observedOct 24, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Goes well beyond the annotations: discloses that it overwrites earlier copy (data-loss behavior despite destructiveHint=false), that it consumes Galatic.AI credits with a pre-check and 402 refusal, that it saves on the episode, and outlines the return shape. This is exactly the extra context annotations cannot carry.

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?

Front-loaded with the deliverable, then behavior (save/overwrite, no posting, credits), then the two parameters that need explanation. Dense but every clause carries information an agent needs to call it correctly.

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?

No output schema exists, and the description supplies the return shape { episode, socialCopy } plus per-platform output contents. Combined with parameter guidance, there is no material gap for correct invocation.

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

Parameters5/5

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

Schema coverage is only 67%, and the description compensates precisely: it explains seriesId as the flowId of the Flow Studio flow holding the series (retrievable via list_flows), and clarifies videoAnalysis's optionality and fallback behavior. episodeId is self-evident.

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?

Names a specific verb (draft ready-to-post captions) and resource (one episode), enumerates the exact platforms and fields produced, and disambiguates from publish_episode by stating 'Posts nothing.' An agent knows exactly what this produces without opening the schema.

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?

Clearly frames usage: videoAnalysis is optional and without it captions fall back to episode title and cast; seriesId is sourced from list_flows. It implicitly excludes publishing but never names publish_episode as the alternative for actually posting, leaving that inference to the agent.

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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