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d3p_post-optimizer

Optimize social media posts by analyzing content and goal to recommend strategic hashtags, timing, and reshare hooks for increased engagement.

Instructions

Optimize social media posts for maximum engagement with strategic hashtags, timing, and reshare hooks. Category: text | Cost: 5 sats | Endpoint: post-optimizer Parameters (pass as JSON string): goal (string) (required): Optimization target: engagement, likes, shares, or followers post_content (string) (required): The draft tweet or X post to optimize

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the burden. It mentions cost (5 sats) and endpoint, but does not disclose whether the action is irreversible, requires authentication, involves AI, or has rate limits. The behavioral impact of 'optimize' is not fully explained.

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 concise, with a clear first sentence stating purpose, followed by metadata (category, cost, endpoint) and parameter list. No redundant information, though the metadata could be considered additional but useful given no annotations.

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

Completeness3/5

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

Given the complexity of a JSON string parameter and the presence of an output schema, the description adequately explains input parameters but fails to describe the output format or behavior. It lacks details on possible values for 'goal' beyond listing them, and does not specify error handling or default behavior.

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

Parameters4/5

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

Schema description coverage is 0%, but the description adds meaning by explaining that the single 'params' string should contain a JSON object with two required fields: 'goal' and 'post_content'. This compensates for the schema's lack of detail and clarifies the parameter structure.

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's purpose: 'Optimize social media posts for maximum engagement with strategic hashtags, timing, and reshare hooks.' It uses a specific verb ('optimize') and resource ('social media posts'), distinguishing it from sibling tools like 'd3p_roast-my-idea' or 'd3p_shitpost'.

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

Usage Guidelines3/5

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

The description implies usage for optimizing posts but lacks explicit when-to-use or when-not-to-use guidance. It does not mention alternatives among siblings, nor does it provide context like prerequisites or limitations.

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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