Formato Specifiche Agenti
Gli agenti Tajo sono definiti in file markdown. Ogni file contiene frontmatter YAML (identità, strumenti, vincoli) e un corpo markdown (istruzioni, strategia, regole). Questo formato si ispira ai pattern di agenti in produzione usati nei sistemi di orchestrazione multi-agente.
Struttura del File
---name: agent-namedescription: What this agent does (max 160 chars)version: 1.0.0temperature: 0.2max_tokens: 4096tools: - brevo_contacts - brevo_email_campaign_management - brevo_sms_campaignstriggers: - event: cart_abandoned - schedule: "0 */4 * * *"permissions: - contacts:read - email:send - sms:send---
# Agent Name
Instructions for the agent in natural language...Campi Frontmatter
Campi Obbligatori
| Campo | Tipo | Descrizione |
|---|---|---|
name | stringa | Identificatore univoco in kebab-case (es. cart-recovery-agent) |
description | stringa | Cosa fa questo agente (max 160 caratteri) |
version | stringa | Versione semantica (es. 1.0.0) |
tools | array | Moduli server MCP Brevo a cui questo agente può accedere |
Campi Comportamentali
| Campo | Tipo | Default | Descrizione |
|---|---|---|---|
temperature | float | 0.3 | Temperatura LLM. Più bassa = più deterministica. Usa 0.1-0.2 per operazioni sui dati, 0.3-0.5 per la progettazione di campagne |
max_tokens | intero | 4096 | Lunghezza massima risposta per turno |
model | stringa | claude-sonnet-4-6 | Modello LLM da usare |
Campi Trigger
| Campo | Tipo | Default | Descrizione |
|---|---|---|---|
triggers | array | [] | Eventi, pianificazioni o webhook che attivano questo agente |
triggers[].event | stringa | - | Nome evento (es. cart_abandoned, customer_created) |
triggers[].schedule | stringa | - | Espressione cron (es. 0 9 * * * per le 9 del mattino quotidiane) |
triggers[].webhook | stringa | - | Percorso webhook (es. /agents/cart-recovery/trigger) |
triggers[].conditions | array | [] | Condizioni filtro per il trigger |
triggers[].debounce | stringa | - | Finestra di debounce (es. 5m, 1h) |
Campi Permessi
| Campo | Tipo | Default | Descrizione |
|---|---|---|---|
permissions | array | [] | Scope di permesso richiesti per la traccia di audit |
related_agents | array | [] | ID agenti a cui questo agente può delegare |
escalation | stringa | - | Dove instradare quando l’agente è incerto (human, supervisor-agent) |
Strumenti: Mappatura ai Server MCP Brevo
Il campo tools fa riferimento ai nomi dei moduli server MCP Brevo. Ogni modulo si mappa a un endpoint specifico su mcp.brevo.com:
tools: # Contacts & Segmentation - brevo_contacts # /v1/brevo_contacts/mcp - brevo_lists # /v1/brevo_lists/mcp - brevo_segments # /v1/brevo_segments/mcp - brevo_attributes # /v1/brevo_attributes/mcp
# Campaigns & Messaging - brevo_email_campaign_management # /v1/brevo_email_campaign_management/mcp - brevo_templates # /v1/brevo_templates/mcp - brevo_sms_campaigns # /v1/brevo_sms_campaigns/mcp - brevo_whatsapp_campaigns # /v1/brevo_whatsapp_campaigns/mcp
# Analytics - brevo_campaign_analytics # /v1/brevo_campaign_analytics/mcp
# Sales CRM - brevo_deals # /v1/brevo_deals/mcp - brevo_companies # /v1/brevo_companies/mcp - brevo_tasks # /v1/brevo_tasks/mcp - brevo_pipelines # /v1/brevo_pipelines/mcp - brevo_notes # /v1/brevo_notes/mcpTip
Usa il set minimo di strumenti di cui il tuo agente ha bisogno. Meno strumenti = migliore ragionamento IA e risposte più veloci. Vedi Server MCP Brevo per tutti i moduli disponibili.
Trigger
Trigger per Evento
Attiva l’agente quando accade qualcosa nel tuo sistema:
triggers: - event: cart_abandoned conditions: - cart_value: "> 50" - items_count: ">= 1" - time_since_activity: "> 30m" debounce: 5mTrigger per Pianificazione
Esegui l’agente su una pianificazione ricorrente:
triggers: - schedule: "0 9 * * MON" # Every Monday at 9am timezone: "America/New_York" - schedule: "0 */4 * * *" # Every 4 hours - schedule: "0 0 1 * *" # First day of each monthTrigger Webhook
Invoca l’agente tramite HTTP:
triggers: - webhook: /agents/win-back/trigger method: POST authentication: api_keyCorpo Markdown: Istruzioni
Il corpo della specifica agente è in linguaggio naturale. Scrivilo come se stessi istruendo un marketer esperto:
Struttura
# Agent Name
Context paragraph, what this agent does and why.
## Strategy
Step-by-step approach the agent should follow.
## Decision Framework
Rules for making choices (e.g., which channel to use based on cart value).
## Rules
Hard constraints, things the agent must ALWAYS or NEVER do.
## Templates
References to Brevo template IDs, SMS copy, WhatsApp templates.
## Metrics
Events to track for measuring success.Scrivere Istruzioni Efficaci
Sii specifico sulla strategia, non solo sugli obiettivi:
## BadRe-engage churned customers.
## GoodWhen a customer hasn't purchased in 90+ days:1. Check their last 3 orders for product category preferences2. Create a personalized discount based on AOV (10% if AOV > $100, 15% if < $100)3. Send email with subject line referencing their preferred category4. Wait 72 hours, if no open, send SMS with discount code5. Wait 7 days, if no purchase, mark as deep-churn and stop sequenceDefinisci i guardrail esplicitamente:
## Rules- NEVER send more than 3 messages per sequence- NEVER contact customers who unsubscribed- ALWAYS check if the customer converted before sending the next step- ALWAYS respect quiet hours (no SMS 9pm-9am local time)- If unsure about a decision, escalate to human reviewCatene Multi-Agente
Per workflow complessi, componi più agenti in una catena. Ogni agente gestisce una fase, passando il contesto al successivo:
name: quarterly-retention-campaignsteps: - agent: customer-intelligence input: | Analyze customer segments for Q2 retention campaign. Goal: {task}
Identify: 1. At-risk customers (declining purchase frequency) 2. VIP customers (top 10% by LTV) 3. Win-back candidates (90+ days since last order)
- agent: campaign-designer input: | Design retention campaigns for these segments: {previous}
Create differentiated approaches per segment: - At-risk: gentle nudge with product recommendations - VIP: exclusive early access or loyalty reward - Win-back: aggressive discount with urgency
- agent: campaign-executor input: | Execute these campaigns via Brevo: {previous}
Use appropriate channels per segment preference. Set up A/B tests for subject lines. Schedule sends for optimal times.
- agent: campaign-reporter input: | Generate the retention campaign launch report: {previous}
Include: segments targeted, campaigns created, expected reach, A/B test configurations.Variabili di Catena
| Variabile | Descrizione |
|---|---|
{task} | L’obiettivo/richiesta originale |
{previous} | Output dal passo precedente |
{step_N} | Output dal passo N (indice 0) |
{artifacts_dir} | Directory per gli output dei file |
Specifiche Agenti Preconfigurati
Campaign Orchestrator
---name: campaign-orchestratordescription: Design and execute multi-channel campaigns from natural language promptsversion: 2.0.0temperature: 0.3tools: - brevo_contacts - brevo_segments - brevo_email_campaign_management - brevo_templates - brevo_sms_campaigns - brevo_whatsapp_campaigns - brevo_campaign_analyticstriggers: - webhook: /agents/campaign/trigger method: POST---
# Campaign Orchestrator
You are a multi-channel marketing campaign specialist.Given a campaign brief, you design, build, and launchcampaigns across email, SMS, and WhatsApp via Brevo.
## Process1. Parse the campaign brief (audience, message, goal, timeline)2. Create or identify the target segment in Brevo3. Select the best channel(s) based on audience preference data4. Build campaign content using existing templates or creating new ones5. Configure send schedule and A/B tests6. Launch and report initial delivery metrics
## Channel Selection- Email: default for all campaigns- SMS: add for time-sensitive offers or cart recovery- WhatsApp: add for conversational campaigns or high-value segments
## Rules- ALWAYS preview campaigns before sending- NEVER send to unsubscribed contacts- ALWAYS set up tracking for campaign attribution- Maximum 2 A/B test variants per campaignCustomer Intelligence Agent
---name: customer-intelligencedescription: Autonomous segmentation, RFM scoring, and churn predictionversion: 1.5.0temperature: 0.2tools: - brevo_contacts - brevo_segments - brevo_attributes - brevo_lists - brevo_campaign_analyticstriggers: - schedule: "0 6 * * MON" timezone: "UTC"---
# Customer Intelligence Agent
You analyze customer data in Brevo to generate actionablesegments and insights for marketing teams.
## Weekly Analysis1. Pull contact activity data from campaign analytics2. Calculate RFM scores (Recency, Frequency, Monetary)3. Identify segment shifts (customers moving between tiers)4. Flag churn risks (declining engagement over 4+ weeks)5. Generate segment recommendations for upcoming campaigns
## Segment Definitions- Champions: R=5, F=5, M=5, recent, frequent, high-value- Loyal: R>=3, F>=4, M>=3, consistent buyers- At Risk: R<=2, F>=3, M>=3, were loyal, now fading- Hibernating: R=1, F>=2, M>=2, long gone, were once active- New: first purchase in last 30 days
## OutputProduce a markdown report with:- Segment sizes and week-over-week changes- Top 10 at-risk customers by LTV- Recommended actions per segment- Suggested campaign themes for the weekDistribuzione
Esecuzione di un Agente in Modo Programmatico
import { TajoAgent } from "@tajo/agent-sdk";
const agent = new TajoAgent({ specPath: "./agents/cart-recovery-agent.md", brevoToken: process.env.BREVO_MCP_TOKEN, model: "claude-sonnet-4-6", // Only connect the MCP servers listed in the agent's tools field autoConnectServers: true,});
const result = await agent.run( "Recover abandoned carts over $50 from the last 4 hours");
console.log(result.summary);console.log(result.toolCalls); // Full audit trailconsole.log(result.metrics); // Events trackedEsecuzione tramite Claude Code
# Point to your agent spec and let Claude execute itclaude "Run the agent defined in ./agents/cart-recovery-agent.md for today's abandoned carts"Pianificazione con Cron
# Run the customer intelligence agent every Monday at 6am0 6 * * MON claude --print "Run ./agents/customer-intelligence.md weekly analysis" >> /var/log/tajo-agents.log 2>&1Passi Successivi
- Server MCP Brevo, Strumenti disponibili e configurazione server
- Creare il Primo Agente, Tutorial pratico
- Riferimento Skill, Skill Tajo che si compongono con gli agenti
- Panoramica Architettura MCP, Come tutto si incastra