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Agent.ai MCP Server

by OnStartups

social_planner_generate_plan_action

Generate a weekly LinkedIn posting plan with 3-7 post ideas mapped to content pillars, including format recommendations, hooks, and timing.

Instructions

Generates a weekly LinkedIn posting plan with 3-7 post ideas, each mapped to a content pillar with format recommendations, hooks, and timing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_pillarsYesComma-separated list of 3-5 content themes (e.g. Leadership, Marketing tips, Customer stories).
planning_periodYesthis_week
specific_topicsNoAny specific topics, product launches, or events to include this week.
num_postsYes5
brand_voiceNo
performance_contextNoOptional JSON from Social Performance Analyzer with top_topics, top_formats, recommendations.
output_variable_nameYesVariable name for the result.social_plan
Behavior3/5

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

No annotations are provided, so the description carries the burden. It mentions the output structure (3-7 post ideas, mapping to pillars, format, hooks, timing) but does not disclose any side effects, API calls, or limitations. For a content generation tool, this is minimally adequate.

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?

The description is a single sentence that front-loads the main purpose and key output details. No redundant information.

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?

Given 7 parameters, no output schema, and no annotations, the description is too minimal. It does not explain the expected input format for performance_context, the output structure in detail, or how this tool relates to its sibling tools like social_planner_render_plan_report.

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

Parameters2/5

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

Schema description coverage is 57% (4 of 7 parameters have descriptions). The description adds context about LinkedIn-specific outputs but does not explain parameters like planning_period, num_posts, brand_voice, or performance_context beyond the schema. It does not compensate for the missing parameter 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 the tool generates a weekly LinkedIn posting plan with 3-7 post ideas, each mapped to a content pillar with format recommendations, hooks, and timing. This distinguishes it from sibling tools like content_planner_generate_content_plan_action, which is more general.

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 on when to use this tool vs alternatives (e.g., social_post_creator_generate_post_action for individual posts, or content_planner_generate_content_plan_action for general content planning). The description does not provide any context on prerequisites or exclusions.

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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