Return all x402/direct-crypto chains DDG supports for AI-agent payment routing.
| Name | Required | Description | Default |
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No arguments | |||
| Name | Required | Description | Default |
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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 provided, so description must fully convey behavioral traits. It implies a read-only operation but lacks details on idempotency, caching, or rate limits. For a simple list query, minimal disclosure is underwhelming.
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?
A single sentence that is concise, front-loaded, and contains no wasted words. Every part earns its place.
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?
The tool is low complexity (0 params) and has an output schema, so description need not explain return values. However, it could mention the list contains chain identifiers or names. Still, minimal context is sufficient for a simple query.
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 has zero parameters, so schema coverage is 100%. Description adds no param info but also has no params to document; baseline 4 is appropriate.
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 verb 'Return' and the resource 'all x402/direct-crypto chains DDG supports for AI-agent payment routing', which is specific and distinct from sibling tools like ddg_direct_crypto_addresses or ddg_checkout_conformance.
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?
No guidance on when to use this versus alternatives (e.g., checking supported chains before querying addresses). With 26 sibling tools, explicit usage context would help but is missing.
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.
