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Brokercheck Individual Detail

brokercheck_individual_detail
Read-onlyIdempotent

Get the full FINRA BrokerCheck profile for one individual broker/adviser rep by CRD number (from brokercheck_search_individual). Returns employment history (current + previous firms) and, when present, the actual disclosure EVENTS — each with event date, disclosure type (e.g. Customer Dispute, Regulatory, Criminal, Financial, Termination), resolution status, and the disclosure detail (allegation/disposition). This is the "is this broker clean, and if not what happened" tool.

Input Schema

NameRequiredDescriptionDefault
crdYesIndividual CRD number (a.k.a. ind_source_id), returned by brokercheck_search_individual.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, non-destructive, and idempotent behavior/TV. The description adds meaningful behavioral context by detailing exactly what gets returned: employment history and, when present, disclosure events with date, type, resolution status, and allegation/disposition. It also signals that disclosure events are conditional ('when present').

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 two sentences, front-loads the main purpose, and packs substantive return details into the second sentence without padding. The final affectionate summary line adds quick decision value and earns its place.

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 single-parameter read-only tool with no output schema, the description is largely complete: it names the input source, the two major return sections, key disclosure fields, and the interpretative purpose. It could be slightly more explicit about whether registration/licensing data is also included, but nothing essential to selecting or invoking the tool is missing.

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?

There is only one parameter, CRD, and the schema already provides 100% coverage, including the alias 'ind_source_id' and provenance from brokercheck_search_individual. The description reinforces the CRD lookup flow but does not add any new meaning beyond the schema, so the baseline of 3 is appropriate.

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: gets the full FINRA BrokerCheck profile for one individual by CRD number. Explicitly connects to brokercheck_search_individual Arena, and the final sentence clarifies its decision value (is this broker clean, and if not what happened). This clearly differentiates it from the firm-oriented sibling and search tools.

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?

The description clearly implies the tool is used after brokercheck_search_individual has supplied the CRD number, and it states the intended purpose. It does not explicitly exclude alternatives such as brokercheck_search_firm, but the 'individual broker/adviser rep' framing and CRD-from-search provenance give adequate usage context.

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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