A lightweight bridge that connects Claude Code to Genudo's Model Context Protocol (MCP) server, enabling AI-powered workflow automation directly from your Claude Code interface.
Analyze a real Genudo conversation to explain the AI agent's behaviour and find the root cause of any drift. Use when the user gives a conversation link or ID, or a client's phone number, and asks what happened, why the agent responded that way, where it went wrong, or why it didn't follow the script. Pulls the…
Analyze a Genudo pipeline's funnel — opportunity counts and distribution across stages, statuses, priorities, and tags — to surface drop-off points and what is converting. Use when the user asks how the funnel is doing, how many leads are in each stage, which tags or segments perform, where leads are stalling, or for…
Draft the pipeline persona (who the agent is and how it sounds) and the global instructions (cross-stage behaviour — product facts, grounding, style, escalation) for a new or existing Genudo pipeline, from a requirements spec. Use after gathering pipeline requirements, or when the user asks to write, rewrite, or…
Design the stages of a Genudo pipeline — for each stage its short name, nature (neutral/won/lost), entry condition (when to enter), the in-stage conversation flow instructions, the data to collect, and any opening message. Use after the persona and global instructions are drafted, or when the user asks to design, lay…
Use to build integrations and automations on a Genudo pipeline — webhook actions to Zapier, Make, n8n, CRMs, or Google Sheets, with the variables that feed them. Handles variable types, payload mapping, triggers, and action-to-action chaining. Use proactively when the user wants the agent to register leads, call an…
Build or update an outbound HTTP action (webhook) on a Genudo pipeline or stage — to Zapier, Make, n8n, a CRM, Google Sheets, or any API. Use when the user wants the agent to register a lead, send data to an external tool, call an API, or trigger an automation. Configures method, URL, headers, payload fields mapped to…
Configure the AI model for a Genudo pipeline — either a single model or a routed model pool with router, simple, moderate, and complex tiers, each with its own provider, model, and instructions. Use when the user wants to change the AI model, set up or tune model routing, or optimize cost versus quality across message…
Configure a Genudo pipeline's operational settings — name, description, max cost per conversation, max messages per conversation, follow-up limit, knowledge-base chunk count, memory window, context size, temperature, and RAG mode. Use when the user wants to cap spend, limit messages, rename a pipeline, change how much…
Set up a stage's opening or outreach message in Genudo — sent automatically when an opportunity enters the stage, either AI-generated or a fixed static message, to the contact's phone. Use when the user wants automatic outreach, a welcome message on stage entry, or a proactive first message to new leads entering a…
Design and push a per-stage follow-up sequence for a Genudo pipeline — timed follow-up messages (for example ten hours after the lead goes quiet), each with drafting instructions and optional assets like videos or materials. Use when the user wants to re-engage silent leads, add a nurture sequence to a stage, or…
Diagnose why a Genudo AI agent is misbehaving and locate the exact fix. Use when the user reports the agent said something wrong, isn't qualifying or closing properly, skips a step, repeats itself, drifts off-script, or fires an action at the wrong time. Maps the symptom to the responsible layer — persona, global…
Interview the user to gather everything needed to build a new Genudo pipeline (an AI sales/support agent) — business objective, channel, products/services, conversation flow, stages, per-stage data to collect, and automations. Use when the user wants to create, build, set up, or design a new pipeline, funnel, sales…
Safely edit a live Genudo agent's instructions — the pipeline persona, the pipeline global instructions, or a stage's instructions or entry condition. Use when the user wants to change, fix, tune, rewrite, or migrate what an existing agent says or does. Loads the current text, edits only what must change, shows a…
The step-by-step safe workflow for editing a live Genudo agent's instructions: load the current text, write the local pipeline mirror, stage the edit, show a before/after diff, get explicit confirmation, push, then record the outcome. Use before any updatepipeline or updatestage call that changes persona…
The Genudo instruction-authoring rules: authoring principles, the pipeline persona + global instructions template, the stage instructions template, and the token-aware quality checklist. Use before writing or rewriting any pipeline persona, pipeline instructions, stage instructions, entry condition or stage aipersona…
Use to curate a Genudo pipeline's knowledge base — the knowledge tables the agent answers from and their rows — when the agent gives wrong or outdated facts. Use when the user reports wrong factual answers, wants to create or fill a knowledge table, or wants to verify what the agent retrieves.
Manage a Genudo pipeline's knowledge base — structured knowledge tables the agent searches at runtime to answer grounded questions. Use when the agent gives wrong or outdated facts, or the user wants to create a knowledge table, add or fix rows, verify what the agent retrieves, or remove stale entries.
Update Genudo opportunities in bulk — change status, move stage, set priority, add notes, or add and remove tags across one or many leads. Use when the user wants to move leads to won or lost, tag a segment, add notes, re-prioritize, or clean up the pipeline. Confirms the exact set before writing; stage moves stay…
Create and manage the variables a Genudo pipeline uses in its actions and webhooks — system variables (opportunity/contact fields), AI-extracted variables (profiled from the conversation), action-output variables (for chaining), and fixed constants. Use when setting up an action that needs data, or when the user asks…
Capture a legacy Genudo pipeline — old persona, old global instructions, old per-stage instructions, and old stage structure — into a structured legacy spec, as the first step of migrating it to the current authoring approach. Use when the user pastes or points to old-format pipeline instructions, or names an existing…
Translate a captured legacy pipeline spec into the current Genudo authoring approach — new persona, global instructions, and stage set written against today's templates — plus a mapping report of what moved where, what was dropped, and what needs a decision. Use after migrate-intake-legacy, or when the user already…
Use to design and build a new Genudo pipeline end to end — from a business goal to a live, product-aware AI sales/support agent with stages, variables, and automations. Delegates the multi-step discovery, authoring, and provisioning. Use proactively when the user wants to create or set up a new pipeline, funnel, or…
Use to diagnose and fix a misbehaving Genudo agent — when it says the wrong thing, drifts off-script, mis-qualifies, fires actions at the wrong time, or a specific conversation went wrong. Analyzes real conversations, root-causes the responsible instruction or action, and applies the fix safely. Use proactively when…
Use to migrate a Genudo pipeline built with an old instructions approach — legacy persona, global instructions, stage instructions, or stage structure — to the current authoring approach. Takes the old artifacts (pasted, from files, or pulled live from the account) and rebuilds or updates the pipeline against today's…
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At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: