AgentReader

uk_officer

Use this to reverse-search a UK Companies House officer name to their appointments (company_number, role, appointed/resigned, status). Returns matches with address_snippet, appointment_count, DOB month/year, high-appointment / mass-formation heuristic flags. Public register (OGL); screening/research aid only - not a credit check. Example: {name:"Ken Olisa",limit:10}. $0.15 USDC. Related: /uk-company $0.50 for full company DD; /kyb $2.50 pack; /uk-leads $1 new cos.

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": {
      "name": "<name>"
    },
    "name": "uk_officer"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`limit`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 5, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and does reasonably well: it discloses the output fields including partial DOB (month/year) and heuristic flags (high-appointment / mass-formation), the data licence (OGL) and the cost ($0.15 USDC). It omits what happens on no match, limit defaults/bounds, and pagination behavior.

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?

Front-loaded with purpose and returns, followed by caveat, example and pricing/routing. Dense but every clause carries information; the pricing and sibling-tool tail is slightly promotional rather than purely functional.

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?

For a 2-parameter lookup with no output schema and no annotations, the description covers purpose, return shape, data provenance, limits of use and cost. The remaining gap is limit semantics and no-match behavior, which an agent would otherwise have to discover by calling it.

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 0% and the schema itself is bare types, so the description must compensate. The worked example {name:"Ken Olisa",limit:10} clarifies that name is a person's officer name and limit caps results, but neither parameter's constraints (max limit, default, partial-name matching) are spelled out.

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?

States a specific verb and resource ('reverse-search a UK Companies House officer name to their appointments') and enumerates the returned fields (company_number, role, appointed/resigned, status), so the agent can tell it apart from uk_company, kyb_report and uk_leads without opening the schema.

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?

Explicitly frames the tool as a 'screening/research aid only - not a credit check' and lists related paid endpoints (/uk-company $0.50 full DD, /kyb $2.50 pack, /uk-leads $1 new cos) that imply when a deeper or different tool is warranted. It does not state an explicit 'use X instead when Y' rule, so it falls just short of a 5.

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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