merchant_snapshotScore an x402 merchant's discovery, reliability, buyer signals, and observed Base USDC activity, then identify the largest revenue issue.
| Name | Required | Description | Default |
|---|---|---|---|
| payTo | Yes | ||
| queries | Yes | ||
| excludePayers | No |
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?
Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about the analytical dimensions and 'observed' Base USDC activity, reinforcing a read-only analysis role, but it does not explain billing despite the $0.05 USDC title note or output behavior.
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 compact sentence with no filler and the core outcome is front-loaded. It is efficient, though it sacrifices parameter clarity for brevity.
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?
Given no output schema and 0% schema description coverage, the description should carry more weight. It conveys the high-level purpose but omits input semantics, output shape, and sibling selection guidance, leaving the tool under-specified for reliable invocation.
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%, yet the description does not explain any of the three parameters: payTo, queries, or excludePayers. An agent cannot determine what 'queries' should contain or why excludePayers exists, making correct invocation largely guesswork.
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 uses a specific verb ('Score') and names a concrete deliverable ('identify the largest revenue issue') with explicit dimensions such as discovery, reliability, buyer signals, and Base USDC activity. It is clear about what the tool does, but it does not explicitly differentiate it from the closely related sibling merchant_audit.
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?
There is no guidance on when to use this tool versus alternatives like merchant_audit, payment_guard, or treasury_preflight. The description states what it does but gives no context about prerequisites, exclusions, or which sibling should be chosen instead.
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.
Several tool pairs have heavily overlapping purposes: check_url vs verify_web_evidence vs batch_check_urls all verify public URLs, while merchant_snapshot vs merchant_audit and payment_guard vs treasury_preflight cover very similar ground. The descriptions clarify some differences, but an agent could easily select the wrong tool when names alone are ambiguous.
All names use snake_case and are readable, but there is no consistent structural pattern. Some start with verbs (check_url, verify_web_evidence), while others are noun compounds (merchant_audit, payment_guard), and batch_check_urls places the verb in the middle. The naming is understandable but not predictable across the set.
At 8 tools, the count is reasonable and within the ideal range for a focused utility server. However, a few tools are near-duplicates of others, so the set feels slightly less well-scoped than the count alone suggests.
For the apparent niche of web3 payment preflight, merchant evaluation, and URL verification, the surface covers the core workflows well. The main gap is the lack of a more granular transaction-history or payment-execution tool, but agents can likely complete their intended tasks without dead ends.