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List personas

persona_list
Read-onlyIdempotent

Ideal-customer definitions used by QUALIFIER steps. usageCount shows how many flows reference each one. A persona describes WHO a lead must be to pass a QUALIFIER step. It is not an AI agent (agent_list, which writes replies) and not a lead tag (tag_list, which classifies replies after the fact). Requires a Pro or Agency plan.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description correctly spends its budget elsewhere: it explains that usageCount reports how many flows reference a persona, and discloses a plan-level entitlement gate. Return shape beyond usageCount is not described, and no output schema exists to cover it.

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 and dense: the core definition comes first, then the usageCount note, then the sibling disambiguation, then the plan requirement. The first and second sentences overlap ('used by QUALIFIER steps' vs 'to pass a QUALIFIER step'), costing a little tightness.

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 parameters, no output schema, and safety fully covered by annotations, the remaining burden is conceptual and entitlement context, both of which are handled. An agent still has no idea what fields a persona record returns besides usageCount, which is the one real gap.

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

Parameters4/5

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

Zero input parameters, so there is nothing to disambiguate and the baseline is 4. The mention of usageCount is a response field rather than a parameter, but it does not confuse the schema, which is empty and closed.

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?

Defines the resource precisely ('ideal-customer definitions used by QUALIFIER steps') and explicitly separates it from two siblings, agent_list and tag_list, with a parenthetical reason for each. The listing verb itself is only carried by the title, not the description text, which keeps it just short of a 5.

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 exclusions are explicit and useful ('not an AI agent... not a lead tag'), and the Pro/Agency plan prerequisite is stated up front, which prevents a failed call. It stops short of telling the agent when to prefer persona_list over persona_get or how to follow up with persona_create/update.

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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