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create_post

Generates another batch of post concepts on an existing campaign ("write more posts for this campaign"). Every post belongs to a campaign in Rebbel today — call generate_campaign first if one doesn't exist yet. For "post this exact text I wrote" instead of another generated concept, use create_adhoc_post.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandIdYesThe brand's id, from list_brands.
campaignIdYesAn existing campaign's id, from generate_campaign or list results.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare mutation (readOnlyHint=false), non-idempotent and non-destructive; the description adds useful behavior beyond them: output is AI-generated concepts rather than deterministic content, and it requires a pre-existing campaign. It does not describe the returned batch shape, but the annotations plus the generation semantics leave little ambiguity.

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?

Three short sentences, front-loaded with the core action, followed by prerequisite and alternative routing. Every sentence carries distinct decision-relevant information with no filler.

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?

For a 2-param mutation tool with full schema coverage and annotations covering the safety profile, the description supplies the prerequisite and the sibling routing, which is what an agent needs to call it correctly. It stops short of describing the returned concept batch, a minor gap with no output schema present.

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% and both parameters (brandId, campaignId) are documented with their sources (list_brands, generate_campaign). The description adds no parameter-level detail beyond what the schema already states, so baseline 3 applies.

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?

States a specific verb+resource ('generates another batch of post concepts on an existing campaign') with a quoted user-intent gloss ('write more posts for this campaign'). It also explicitly distinguishes itself from create_adhoc_post, so an agent can route without opening either schema.

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?

Gives an explicit precondition (call generate_campaign first if none exists) and names the alternative tool with the exact condition that selects it ('post this exact text I wrote' → create_adhoc_post). When-to-use and when-not-to-use are both covered.

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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