Generate 1/1 hand-drawn mfer art in the style of sartoshi (CC0) — thin wobbly ink lines, naive doodle style. Output is public domain. [PAID: $0.069 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?
Without annotations, the description discloses that output is public domain, paid (via x402), and async (returns job_id). No contradictions detected.
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 a single sentence with essential details (purpose, style, output license, cost, async behavior), efficiently front-loaded.
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?
Covers purpose, style, licensing, cost, and async nature. Lacks details on polling mechanics, but given the single parameter and no output schema, it is fairly complete.
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?
Schema coverage is 100% with the parameter 'prompt' described as 'Input prompt for this service.' The description adds stylistic context but no additional parameter-level semantics 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 'Generate 1/1 hand-drawn mfer art in the style of sartoshi (CC0)' with specific stylistic details, distinguishing it from sibling art generators.
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 includes cost and async behavior but lacks guidance on when to use this tool versus other art generators like darkfarms-gen or hokusai-gen.
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.
