Pass/fail trust verdict for any AI agent across ERC-8004, Olas, or Virtuals registries. Returns score, tier, badges, and reasoning.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Agent ID (token ID or Mech ID) | |
| chain | Yes | Chain slug: ethereum, base, bnb, gnosis, avalanche, celo, arbitrum, polygon, monad, megaeth, optimism | |
| registry | No | Registry: erc8004 (default), olas, virtuals | |
| threshold | No | Pass/fail threshold (default 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states what the tool returns but does not disclose side effects, permissions, idempotency, failure modes, or whether it performs any writes. This is minimal transparency for an unannotated tool.
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 with no filler. It front-loads the core purpose and then lists the return fields, making it easy to scan and process.
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 the moderate complexity and absence of an output schema, the description provides a useful summary of return values (score, tier, badges, reasoning) and covers the registries. It does not mention edge cases or error behavior, but for a check-like tool the provided context is largely adequate.
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 coverage is 100%, so all four parameters already have descriptive meaning. The description adds a small amount by framing the result as a pass/fail verdict with score, tier, badges, and reasoning, but does not enrich parameter semantics beyond the schema.
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 phrase 'Pass/fail trust verdict' with a clear resource ('any AI agent') and scope ('across ERC-8004, Olas, or Virtuals registries'). It differentiates from siblings like compare_agents and risk_terms by focusing on trust verdicts with output types.
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?
The description clearly implies this tool is for obtaining a trust verdict on an AI agent, giving context for when to use it. It does not explicitly exclude alternatives or mention when not to use it, but the context is clear enough for selection.
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.
Most tools have distinct purposes, but reviewer_analysis and reviewer_wallet overlap in analyzing reviewer behavior, and trust_check and risk_terms both provide trust assessments with different framing. Descriptions help clarify the differences, yet an agent could easily misselect between these pairs.
All tool names use snake_case, but the pattern is inconsistent: some are verb_noun (compare_agents, trust_check) while others are noun-based (address_age, entity, mcp_attestation). This mixed convention is readable but not predictable.
10 tools is well-scoped for an AI agent trust intelligence server, covering both individual lookups and network-wide statistics without unnecessary redundancy. Each tool addresses a specific analytical need.
The server covers the core trust intelligence surface: trust scores, risk assessment, wallet profiling, reviewer analysis, commerce stats, and network stats. Minor gaps exist, such as no tool to fetch a single agent's full profile independent of an operator, but overall the domain is well covered.