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1036007003-wq

linkedin-marketing-mcp

optimize_linkedin_post

Optimize your LinkedIn post draft for higher engagement by tailoring it to your target audience.

Instructions

PREMIUM: Optimize a LinkedIn post for maximum engagement. Requires DEESEEK_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
post_draftYesYour draft LinkedIn post
target_audienceYesTarget audience (e.g. "B2B marketers", "AI engineers", "startup founders")
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only states purpose and a requirement (API key), but does not disclose what the tool returns (e.g., optimized text, suggestions) or any behavioral traits like 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is brief with two sentences, front-loading the main purpose. However, it lacks structure and could be more informative without adding length.

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 tool with no output schema and no annotations, the description should clarify the return format and behavior. It only states purpose and a precondition, leaving the agent with significant unknowns about how to use the output.

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 100% with descriptions for both parameters. The description adds no further meaning beyond the schema, so baseline 3 is appropriate.

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?

Tool name and description clearly state it optimizes a LinkedIn post for engagement. The verb 'optimize' and resource 'LinkedIn post' are specific. It distinguishes from sibling tools which focus on analysis and connection requests, though it does not explicitly differentiate.

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 versus alternatives. It notes it is 'PREMIUM' and requires an API key, but provides no context on when not to use it or what alternative tools exist for similar tasks.

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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