robyn_message_anchor_proofMerkle inclusion proof for an anchored row id: leaf, path, root, the signer’s EIP-191 signature over the batch statement and the on-chain tx when enabled. Verify locally with plus-sdk verifyAnchorProof(). Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | 16-hex feed row id |
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, the description carries the full burden and does so impressively. It explicitly states 'Read-only', lists the expected proof fields, and discloses the conditional 'when enabled' for the on-chain transaction. It could mention error behavior but covers the essential operational traits well.
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 concise yet information-dense, pack intent, content, verifiability, and safety into a few lines. No filler or redundancy.
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?
For a single-parameter tool with no output schema, the description covers the proof contents, the verification method, the conditional transaction field, and the read-only nature. This fully compensates for missing structured metadata.
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 schema already fully describes the single parameter as a '16-hex feed row id' (100% coverage), and the description's 'anchored row id' adds no new semantics. A baseline of 3 is correct since the schema handles the parameter documentation without needing additional description.
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 identifies the tool as providing a Merkle inclusion proof for an anchored row id and specifies the proof components. It doesn't explicitly contrast with sibling proof/verification tools, so it's clear but lacks direct sibling differentiation.
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?
It gives practical guidance to 'Verify locally with plus-sdk verifyAnchorProof()', which implies how to use the output, but it doesn't position this tool against alternatives or state when not to use it. Usage context is conveyed only through the proof purpose, so it's barely adequate.
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.
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.