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tcgenerate-random

Generate a random AI trading-card image by TCGenerate — a fully autofilled collectible card (name, subject, action, background, art style). Takes no input. Re-brokered over x402; output pinned to IPFS. [PAID: $1.005 USDC per call via x402; async — returns a job_id to poll]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesInput prompt for this service.

TDQS

C2.2/5.0
Behavior1/5

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

No annotations provided, so description must disclose behaviors fully. While it mentions paid async operation, it claims 'Takes no input' but the schema requires a 'prompt' parameter. This severe contradiction undermines transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

The description is relatively brief but wastes space by including a false statement ('Takes no input'). The pricing and async details are useful, but the contradiction reduces efficiency.

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?

With no output schema, the description should cover return values and usage flow. It mentions returning a job_id but does not explain the final output. The input contradiction also makes it incomplete.

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

Parameters1/5

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

Schema coverage is 100%, so the baseline is 3, but the description directly contradicts the schema by stating no input is needed while the schema requires a prompt. This adds confusion rather than value.

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?

The description clearly states the tool 'Generate a random AI trading-card image', which is a specific verb-resource pair. It distinguishes from sibling generation tools by emphasizing 'random' and 'autofilled'. However, the contradiction with the input schema reduces clarity slightly.

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 explicit guidance on when to use this tool versus alternatives like darkfarms-gen or hokusai-gen. The description notes it is 'random' and 'paid' but fails to provide decision-making context.

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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TDQS

A3.7/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness4/5

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.