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Agent.ai MCP Server

by OnStartups

social_post_creator_generate_post_action

Create LinkedIn posts with hook, body, CTA, hashtags, and optional AI-generated images. Choose text or image format, set brand voice and colors.

Instructions

Creates a complete LinkedIn post with hook, body, CTA, hashtags, and optional AI-generated image sized for LinkedIn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesWhat is this post about? Be specific for best results.
post_formatYestext
image_styleNoOnly applies when format is Image Post.conceptual
image_aspect_ratioNoPortrait takes up more feed space on mobile.portrait
key_pointsNoAny specific data, anecdote, or angle to include.
cta_intentNoengage
link_urlNoOnly used when CTA goal is Visit Link. Placed in first comment, not post body.
content_pillarNoWhich content pillar this post maps to.
brand_voiceNo
brand_primary_colorNoHex code (e.g. #1d4ed8). Used as the dominant color in generated images.
brand_secondary_colorNoHex code (e.g. #f59e0b). Used as accent color in generated images.
brand_logo_urlNoS3 or public URL to brand logo (PNG/SVG). Used in quote cards and infographics.
output_variable_nameYesVariable name for the result.social_post
Behavior3/5

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

With no annotations, the description partially discloses behavior (creates post, optional image) but does not clarify whether it actually posts to LinkedIn or just generates content, nor does it mention permissions, rate limits, or side effects.

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?

One concise sentence that lists key components with no wasted words. It is front-loaded and efficient.

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?

Despite having 13 parameters and no output schema, the description is too brief. It does not explain return values, whether the post is published, image generation details, or prerequisites like brand assets.

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 coverage is 77% (high), so the description's summary of components adds some value but does not explain parameter details beyond the schema descriptions.

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 clearly states it creates a LinkedIn post with specific elements (hook, body, CTA, hashtags, optional AI-generated image) and distinguishes it from related sibling tools like social_planner and social_performance_analyzer.

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?

No guidance is provided on when to use this tool versus alternatives such as social_post_creator_generate_social_image_action or content_creator_generate_article_action. The context of usage is implied but not explicitly stated.

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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