Verify an AI agent by its DID.
Checks whether the DID is registered and returns verification status
along with the agent's trust card (reputation, credentials, blockchain anchor).
Args:
did: Decentralised identifier (e.g. "did:moltrust:a1b2c3d4e5f60718")
| Name | Required | Description | Default |
|---|---|---|---|
| did | Yes | Decentralised identifier (e.g. "did:moltrust:a1b2c3d4e5f60718") |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / did / descriptionAdded value: +"Decentralised identifier (e.g. \"did:moltrust:a1b2c3d4e5f60718\")"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds value by disclosing the payload shape (registration status plus reputation, credentials, blockchain anchor), but leaves open what happens for an unregistered DID — error versus a negative status — and says nothing about cost, rate limits, or whether calls are metered against credits.
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?
Two front-loaded sentences state the action and the result before any detail. The trailing Args block is largely redundant with a 100%-covered schema, a small amount of waste but not enough to undermine the structure.
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?
With an output schema present, the return-value description need not be exhaustive, and one required parameter with full schema coverage keeps the surface simple. The remaining gap is behavioral: no statement of the unregistered/nonexistent-DID outcome, which matters for an agent branching on the result.
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 100% and the single parameter is fully documented in the schema; the description's Args block restates that text verbatim rather than adding format constraints, alternate DID namespaces, or expected failure modes. Baseline 3 applies when the schema already carries the parameter semantics.
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?
Specific verb (verify) plus resource (an AI agent identified by DID), with a concrete statement of what is checked and returned. It does not distinguish itself from the many sibling verify tools (molcheck_verify, moltproof_verify, mt_*_verify), so an agent cannot tell from the text alone which verification surface this belongs to.
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?
Usage is implied by the verb — an agent would call this to check whether a DID is registered — but there is no explicit when-to-use, no prerequisites (e.g. does the agent need to be registered first?), and no routing away from the similarly named verification siblings.
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.