robyn_payment_request_settlementAfter paying, prove it: re-checks the transfer against the DESTINATION CHAIN and confirms the payee was paid at least the amount requested. Returns paid=true only on a verified on-chain result; paid=null means undetermined, which is NOT evidence you satisfied the request.
| Name | Required | Description | Default |
|---|---|---|---|
| request | Yes | ||
| signature | Yes | ||
| transferId | Yes | the transfer that paid it |
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?
With no annotations provided, the description fully carries the behavioral burden. It discloses the verification logic, the meaning of paid=true (verified on-chain result) and paid=null (undetermined, not evidence), which is crucial for correct interpretation.
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 two sentences, front-loaded with 'After paying, prove it', and every sentence adds necessary behavioral insight. No redundant or filler content.
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 description adequately covers the core purpose and primary return semantics (paid=true/null), but with no output schema it does not fully explain the complete response shape or the role of request/signature parameters. It is usable but has gaps for a 3-parameter tool with nested objects.
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 only 33% (only transferId has a description). The description adds no explicit meaning for the 'request' object or 'signature' string, and only indirectly relates to the transfer via the transferId. It does not compensate for the schema gaps.
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 a specific verb and resource: 'prove it' by re-checking the transfer against the DESTINATION CHAIN and confirming the payee was paid. It differentiates from siblings by emphasizing on-chain verification and the payee amount requirement.
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?
Provides clear context: 'After paying, prove it' indicates when the tool should be used. However, it does not explicitly mention alternatives or when not to use it, which would fully distinguish it from sibling tools like robyn_payment_request_verify.
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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Many tools have overlapping purposes, such as robyn_quote, robyn_prepare, robyn_settle, robyn_cross_chain, robyn_plan, robyn_preflight, and robyn_preflight_full, all involving routing or quoting. Although descriptions are detailed, the high number of subtly different tools makes selection error-prone.
All tools follow a consistent <prefix>_<verb/noun> pattern, with robyn_ and null_ as clear category prefixes. Verbs like prepare, submit, verify and nouns like quote, plan, mesh are highly predictable throughout.
With 70 tools, the count far exceeds the 25+ heavy threshold. While the service scope is broad (payments, messaging, netting, Plus, yield, etc.), many tools could be merged or tiered, making the set feel overly large and burdensome for an agent.
The surface covers the full lifecycle from quoting, planning, submitting, verifying, auditing to messaging, custody, yield, and mandates, plus sandbox, lint, and recipes. A few advanced operations like cancellation or revocation are missing, but no critical gaps remain.