LLPRO Campus

Look up an agent or tool

agentrecord_lookup

Read-onlyIdempotent

Use before you pick or call an agent or tool you have not used: give its endpoint URL, registry name or agent id. Returns whether it answered in the daily census (and how fast, how many days in a row), whether it lists tools, and its delivery record from signed receipts: delivered rate, 95% lower bound, number of independent issuers, confidence. Free; no paid placement.

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": {
      "target": "<target>"
    },
    "name": "agentrecord_lookup"
  }
}

Input Schema

Name	Required	Description	Default
`target`	Yes	Endpoint URL, registry name (e.g. ai.llpro.countersign/countersign) or agent id

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real value by disclosing data provenance (daily census and signed receipts, independent issuers) and a bias statement ('Free; no paid placement'). It omits what happens on an unknown target, rate limits, and pagination, so it is solid but not rich.

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

Conciseness4/5

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

Two sentences, front-loaded with the usage trigger, then the return contract. Every clause carries information; the return-field enumeration is dense but justified because no output schema exists.

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

Completeness4/5

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

With no output schema, the description carries the burden of explaining returns and does so thoroughly, including the confidence measure. It falls short only on failure behavior for a missing or malformed target, which an agent would want before calling.

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

Parameters3/5

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

Schema coverage is 100% and the single 'target' parameter is already documented with the same accepted formats and example. The description only restates those formats, adding no meaning beyond the schema, which is the baseline 3 case.

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

Purpose4/5

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

States a specific verb and resource ('look up an agent or tool') and then enumerates the returned evidence (census answer, response speed, streak, delivery rate, lower bound, issuer count). That return-content list distinguishes it from neighbors like agentrecord_census or certified_lookup, though no sibling is named explicitly.

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

Usage Guidelines4/5

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

Gives a concrete trigger: 'Use before you pick or call an agent or tool you have not used.' This is clear when-to-use guidance, but there are no stated exclusions or named alternatives for cases like already-known agents or bulk discovery.

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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