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generate_content

generate AI content for a launch's platforms using Claude

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": {
      "id": "<id>"
    },
    "name": "generate_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYeslaunch ID
platformsNospecific platforms to generate for (defaults to all launch platforms)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the basic safety profile is supplied. The description adds only that Claude is used and that generation targets launch platforms; it does not disclose whether existing content is overwritten, whether generation is synchronous or long-running, or what side effects occur.

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 description is a single compact sentence with no filler, and the core action is front-loaded. It is appropriately sized, though its terseness contributes to the gaps in usage and behavioral detail.

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

Completeness2/5

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

For a generation tool with two parameters, a non-read-only annotation, no output schema, and siblings like retry_launch_content and generate_media, the description is incomplete. It omits routing guidance, side-effect expectations, and any indication of what generation produces or returns.

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 description coverage is 100%, so both the launch ID and platforms parameters are already documented by the schema. The description mentions platforms and the launch context but adds no syntax, default behavior, or platform-specific meaning beyond what the schema provides.

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: generating AI content for a launch's platforms, and mentions Claude as the engine. It is distinguishable from generate_media by saying content rather than media, but it does not explicitly differentiate itself from retry_launch_content or clarify whether it creates new content versus replacing existing drafts.

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

Usage Guidelines2/5

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

The description gives no when-to-use guidance, no exclusions, and no alternatives. It does not explain when an agent should call generate_content rather than generate_media or retry_launch_content, leaving usage entirely inferred from the tool name and purpose statement.

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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