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Find people, agents or clients

find_people
Read-only

Fuzzy-search for a worker, teammate, or client by name, handle, or email. Use this to disambiguate a plain-language reference (e.g. 'Merrilee' or 'Avalore') before create_task/handoff_task. Returns ranked candidates with handles you can pass back, plus needs_disambiguation when the top hit is semantically ambiguous. active_agency is always included so callers can see which org was in effect. API reference: https://tango.applayer.io/docs/api/tools/find_people

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoFilter by kind. Default 'any' — kinds are interleaved by score.
limitNo
queryYesFree text: a name, first name, @handle, or email.
scopeNo'active_agency' (default) or 'global' across all orgs the caller can see.
agency_idNoRestrict to a specific agency (defaults to active agency).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the read-only, non-destructive profile, so the bar is lower. The description adds real behavioral value beyond that: it discloses the ranked-candidate return shape, the needs_disambiguation flag, that handles are pass-back usable, and that active_agency is always included even for global scope.

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?

Three tight sentences, front-loaded with purpose before usage and return notes. The trailing API reference URL is slightly extraneous but low-cost and clearly demarcated.

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 and one required parameter, the description usefully compensates by explaining the return shape (ranked candidates, handles, needs_disambiguation, active_agency). What remains thin is scope/agency filtering behavior, but overall it gives an agent enough to call and interpret the tool.

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 description coverage is 80% with two enums already documented, so the schema does the heavy lifting. The description restates that query accepts name/handle/email but adds no syntax or constraint detail beyond what the schema provides; baseline 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 ('fuzzy-search') and resource ('worker, teammate, or client') with the input modes (name, handle, email). This clearly differentiates it from exact-match siblings like resolve_mention, whoami, and list_agents.

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 an explicit when-to-use with a trigger scenario ('disambiguate a plain-language reference before create_task/handoff_task') and concrete examples. It does not state when NOT to use it or contrast against nearby alternatives like resolve_mention or list_agents, so it stops 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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