Turn any image into a mfer in the mferGPT house style. Pass an image URL as the prompt. Re-brokered over x402. [PAID: $0.055 USDC per call via x402; async — returns a job_id to poll]
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | Input prompt for this service. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears transparency. It discloses paid cost ($0.055 USDC), async nature (returns job_id to poll), and re-brokering over x402. However, it does not detail privacy or data handling, which is a minor 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?
The description is concise: two sentences plus a bracketed note. It front-loads the main purpose and provides all key information without redundancy. Every sentence adds value: purpose, input format, cost, and async behavior.
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?
For a simple tool with one parameter and no output schema, the description is fairly complete. It explains the input (image URL), payment, and async polling. However, it omits details like polling endpoint, output format, or image size limits, which would enhance completeness.
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?
The schema has 100% coverage for the only parameter 'prompt' but only describes it as 'Input prompt for this service.' The description adds critical meaning by specifying 'Pass an image URL as the prompt,' which uniquely defines the input format beyond the schema.
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 clearly states the tool's purpose: 'Turn any image into a mfer in the mferGPT house style.' It specifies the action (turn), the input (image), and the output style (mfer), distinguishing it from sibling gen tools that apply different styles.
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?
The description implies usage by saying 'Pass an image URL as the prompt' but does not explicitly state when to use this tool versus alternatives like hokusai-gen or monet-gen. No when-not or exclusion criteria are provided, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: data query (cc0pedia*), market data, daily brief, art generation by specific artists, mfergpt interactions, and random card generation. No two tools overlap in functionality.
Names are consistently lowercase with hyphens, and within each subgroup (e.g., `-gen` for generation, `cc0pedia-` for data tools), patterns are clear. However, there is no single verb_noun pattern across all tools, with some being proper names (cc0-daily-brief) or suffixed with `-ask`, `-lore`, etc.
14 tools is well-scoped for the server's purpose, covering CC0 data retrieval, art generation, and a chatbot. Each tool adds distinct value without overwhelming the set.
The server covers core operations: CC0 data lookup, search, verify, market, daily brief; four distinct art generation styles; mfergpt Q&A, lore, and image transformation; plus random card generation. A minor gap is the lack of a tool to list available art styles or a general-purpose CC0 art explorer, but essential workflows are present.
