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Moe03

Convocore MCP Server

by Moe03

generate_lead_funnel

Read-onlyIdempotent

Generate lead-funnel qualification stages and scoring from an agent prompt using AI, returning suggested steps to save via update_agent.

Instructions

Draft lead-funnel steps (qualification stages and scoring) from an agent prompt with AI. Returns the suggested steps only — save them with update_agent funnelConfig. Pass the agent prompt text; get it from get_agent if needed. Actions: generate — suggest funnel steps

Input Schema

NameRequiredDescriptionDefault
modeNocompact (default) = light mode: long text is cut and bulky blobs are replaced by a size marker. full = complete API response.
actionYes
userNotesNoExtra guidance, e.g. what a hot lead means for this business.
agentPromptYesThe agent instructions to analyse.
existingStepsNoCurrent steps to refine instead of starting over.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.6.17

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive, open-world behavior. The description adds important context beyond those hints: the tool drafts suggestions with AI and does not persist them, so the agent knows a separate update_agent call is required to save.

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 short, front-loaded with the core action, and every sentence carries useful information. It moves efficiently from purpose to return behavior to parameter sourcing to action enumeration.

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?

There is no output schema, and the description compensates by stating that the tool returns suggested steps only. It covers the save path and prompt source, which are the main operational details. It could mention the existingSteps refinement path, but the remaining schema fields are documented.

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%, so most parameters are already documented in the schema. The description adds useful sourcing guidance for agentPrompt via get_agent, but it does not explain existingSteps, userNotes, or mode beyond what the schema already says. Baseline 3 is appropriate when the schema does most of the work.

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?

The description states a specific verb and resource: drafting lead-funnel qualification stages and scoring from an agent prompt using AI. It clearly distinguishes this from update_agent, which is named as the save path, so an agent can tell what this tool does and does not do.

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 explains that the tool returns suggested steps only and that they must be saved separately with update_agent funnelConfig. It also tells the agent to pass agent prompt text and get it from get_agent if needed. It does not give explicit exclusions, but the context is clear enough to select the tool.

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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