x402-ai-prompt-optimize
AI Prompt Optimize: Improve your AI prompts for better output.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | ||
| prompt | No |
AI Prompt Optimize: Improve your AI prompts for better output.
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | ||
| prompt | No |
Changes observed during successful MCP inspections.
Input schema / properties / prompt / descriptionRemoved value: -"Prompt to process"Input schema / properties / text / descriptionRemoved value: -"Text to process"Input schema / properties / textAdded value: +{
+ "description": "Text to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: it does not say whether the tool returns a rewritten prompt, a critique, or a score, whether the call is a paid/metered x402 request, or what happens on malformed input. For a tool whose only stated function is a transformation, this is a complete disclosure gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is a single short sentence with no redundancy and the resource is front-loaded. However, brevity here is under-specification rather than economy: the trailing clause 'for better output' is pure filler that consumes the one sentence available for substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, 0% parameter coverage, and two mutually ambiguous string inputs, the description would need to supply the entire contract; it supplies none of it. An agent has no information about inputs, outputs, cost, or side effects, making correct invocation essentially guesswork.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Two parameters ('text' and 'prompt') exist with 0% schema description coverage and zero required fields, and the description mentions neither. It leaves the central ambiguity unresolved: whether 'prompt' is the prompt to optimize and 'text' is supporting context, or the reverse — an agent cannot reliably construct a call.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description restates the tool name almost verbatim ('AI Prompt Optimize' → 'Improve your AI prompts') and adds only the marketing phrase 'for better output,' which conveys no concrete operation. It never says what 'optimize' means here (rewrite, restructure, add role/constraints) nor separates it from siblings like x402-ai-rewrite, x402-prompt-templates, or x402-ai-ask.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use, when-not-to-use, or alternative-tool guidance, which matters acutely in a catalog containing dozens of x402-ai-* and prompt-related siblings. The domain is implied by the phrase 'AI prompts,' so it is not actively misleading, but an agent gets no basis for choosing this tool over x402-ai-rewrite.
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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