Triggers the Cradle Father-Agent to breed a child AI model on RunPod. Returns a Job ID to track progress. Requires an x402 payment signature covering $10 USDC for compute.
| Name | Required | Description | Default |
|---|---|---|---|
| base_model | No | Optional base model hint | |
| target_task | No | The NLP task (e.g. text-classification, summarization) | |
| payment_signature | No | Base64 x402 PAYMENT-SIGNATURE header value (v2 preferred). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond the destructiveHint annotation: it reveals that the tool is asynchronous (returns a Job ID) and requires a payment signature. This helps the agent understand the side effects and prerequisites.
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 extremely concise with two sentences covering purpose, output, and a critical requirement. No redundant or unnecessary information.
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?
While the description explains the return value (Job ID) and payment requirement, it could provide more context on the base_model and target_task parameters. However, given the schema descriptions are complete, the overall completeness is adequate for an action-triggering tool.
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 input schema already provides 100% coverage with descriptions for all parameters. The tool description does not add any additional guidance on parameter usage or formatting, so it meets the baseline but does not exceed.
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 action: 'Triggers the Cradle Father-Agent to breed a child AI model on RunPod' and mentions the return of a Job ID. This is specific and distinguishes it from siblings like merge_models or search tools.
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 mentions the requirement of an x402 payment signature, which is a key condition for use. However, it does not explicitly indicate when not to use this tool or provide alternative tools for similar tasks, such as merge_models for model combination.
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.
Most tools have clearly distinct purposes, but the deprecated tools (list_datasets, list_market_apis, search_datasets, try_dataset) overlap with modern replacements (search_catalog, get_listing). Some functional overlap exists between get_activity and charge_list, but descriptions clarify their scopes. Overall, an agent can usually tell tools apart, with a few legacy remnants.
Tool names follow a consistent snake_case verb_noun pattern (browse_catalog, business_start, charge_create, etc.). Even the deprecated tools adhere to the same style. There are no mixed conventions or vague verbs like 'process' or 'run'. The naming is highly predictable.
At 52 tools, this is a large surface. The domain is broad (marketplace buying/selling, business management, policy, storefront, distribution, authentication), so many tools are justifiable. However, four deprecated tools could be pruned, and the count is on the heavy side compared to typical MCP servers. It feels overengineered, yet each tool addresses a distinct facet of the platform.
The toolset covers the full lifecycle: discovery, evaluation, purchase, delivery, feedback, business management, policy, storefront, and distribution. Gaps are minor—for example, no direct way to list all services with full details without service_list, but that exists. The deprecated tools indicate ongoing migration to a consolidated search surface, suggesting good coverage. A few small gaps remain (e.g., no explicit 'update listing' for buyers, but that may not be needed).