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web3-agents-mcp

web3-agents-mcp

by hanjoonchoe
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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get_validations

Retrieve an agent's validation registry entries, including validator, method classification, response, and timestamp. Zero validations count as a normal result.

Instructions

Reads an agent's Validation Registry entries (validator, best-effort method classification, response, timestamp). An agent with zero validations is a normal, successful result — not an error.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agentId": "<agentId>"
    },
    "name": "get_validations"
  }
}

Input Schema

NameRequiredDescriptionDefault
chainNoChain to query, by name (see list_chains). Defaults to base.
limitNo
offsetNo
agentIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full transparency burden. It does disclose that the operation is a read and explains that an empty result is normal (a useful behavioral clarification). However, it omits details on pagination behavior (limit/offset), chain handling, and any potential side effects or errors, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally concise: two sentences, front-loaded with the action and resource, and the second sentence adds a valuable clarification without any fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has four parameters, no output schema, and no annotations, so the description must compensate. It provides a partial return-value description (entry fields) and the zero-validations clarification, but fails to cover pagination, chain switching, or how this differs from related trust/reputation tools. It is adequate but leaves clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is low (25%, only chain described). The description does not explain agentId, limit, offset, or chain semantics. It mentions the content of returned entries, which indirectly relates to what data is fetched, but it does not help an agent understand how to fill the parameters or what each parameter controls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Reads') and resource ('Validation Registry entries'), and enumerates the entry content (validator, method classification, response, timestamp). This clearly distinguishes it from sibling tools like get_reputation or assess_trust, which focus on different aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives such as get_reputation or assess_trust. The note about zero validations being a normal result is a result-interpretation hint, not a usage-selection criterion, so it does not satisfy the 'when-to-use vs alternatives' requirement.

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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