Submit a paid operator-reviewed DDG order after caller supplies valid payment headers/proof.
| Name | Required | Description | Default |
|---|---|---|---|
| request | Yes | ||
| agent_id | No | ||
| service_id | Yes | ||
| payment_headers | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
No annotations are provided, so the description must disclose behaviors. It mentions 'operator-reviewed' indicating a manual step, but does not detail what happens after submission (e.g., asynchronous, returns order ID). The presence of an output schema reduces the burden, but more context on the review process would improve transparency.
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 of 14 words, making it concise. However, it is too sparse given the tool's complexity and the lack of schema descriptions, leaving critical details unaddressed.
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 4 parameters, a nested object, and an output schema, the description is incomplete. It does not explain the 'request' object, how to obtain 'service_id', or the format of 'payment_headers'. The output schema may help, but the description should still provide overall workflow context.
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 description coverage is 0%, so the description must compensate. It only explains 'payment_headers' (as 'payment headers/proof'), but fails to describe 'request', 'agent_id', and 'service_id'. This is a significant gap for a 4-parameter tool with nested objects.
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 action 'Submit' and the resource 'paid operator-reviewed DDG order', with a prerequisite condition. This distinctively differentiates it from sibling tools like ddg_order_status or ddg_quote_payment.
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 when to use: after obtaining valid payment headers/proof. However, it does not explicitly state when not to use or list alternatives, but the context is clear.
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, ranging from status checks to order management to payment processing. Despite the large number, descriptions make them easy to differentiate, with no obvious overlap.
All tools share the 'ddg_' prefix, but naming patterns vary: some use verb_noun (e.g., ddg_list_models) while others use noun_noun (e.g., ddg_agent_status). This mix reduces consistency, though readability remains acceptable.
With 25 tools, the count is at the high end but scales to cover diverse aspects of payable services (status, orders, payments, models, x402). Minor consolidation could be possible, but most tools earn their place.
The tool surface covers core workflows like order lifecycle, payment, and service discovery. Minor gaps (e.g., no cancellation or refund tools) exist but do not severely hinder typical agent interactions.
