ddg_order_artifact
Fetch an agent-scoped DDG order artifact when ready.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | ||
| order_id | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
DDG Agent Services
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3.3/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only says 'fetch', implying a read operation. It does not disclose what happens if the artifact is not ready, required permissions, or potential side effects. The behavioral disclosure is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words, efficiently conveying the core action and key constraints. It is front-loaded and earns its place.
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?
Given the tool's moderate complexity (two params, many siblings), the description omits preconditions, error handling, and the nature of the artifact. The output schema is present but does not compensate for missing usage and behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%—the description does not explain the parameters. The phrase 'agent-scoped' hints at agent_id's role, but order_id is left implicit. No detail on format or constraints is added beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'DDG order artifact', and specifies scoping ('agent-scoped') and condition ('when ready'). It distinguishes from sibling tools like ddg_order_status (which provides status) and ddg_submit_order (which submits orders).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'when ready' implies usage context but does not explicitly state preconditions (e.g., check order status first) or provide alternatives. No exclusions or comparisons to siblings are given.
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
B3.2/5.0
Disambiguation5/5
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.
Naming Consistency3/5
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.
Tool Count4/5
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.
Completeness4/5
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.