Agent-Spezifikationsformat
Tajo-Agents werden in Markdown-Dateien definiert. Jede Datei enthält YAML-Frontmatter (Identität, Tools, Einschränkungen) und einen Markdown-Textkörper (Anweisungen, Strategie, Regeln). Dieses Format ist von Produktions-Agent-Mustern in Multi-Agent-Orchestrierungssystemen inspiriert.
Dateistruktur
---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...Frontmatter-Felder
Pflichtfelder
| Feld | Typ | Beschreibung |
|---|---|---|
name | string | Eindeutiger Bezeichner in kebab-case (z. B. cart-recovery-agent) |
description | string | Was dieser Agent tut (max. 160 Zeichen) |
version | string | Semantische Version (z. B. 1.0.0) |
tools | array | Brevo MCP-Server-Module, auf die dieser Agent zugreifen kann |
Verhaltensfelder
| Feld | Typ | Standard | Beschreibung |
|---|---|---|---|
temperature | float | 0.3 | LLM-Temperatur. Niedriger = deterministischer. 0.1-0.2 für Datenoperationen, 0.3-0.5 für Kampagnenentwurf |
max_tokens | integer | 4096 | Maximale Antwortlänge pro Runde |
model | string | claude-sonnet-4-6 | Zu verwendendes LLM-Modell |
Trigger-Felder
| Feld | Typ | Standard | Beschreibung |
|---|---|---|---|
triggers | array | [] | Events, Zeitpläne oder Webhooks, die diesen Agent aktivieren |
triggers[].event | string | - | Event-Name (z. B. cart_abandoned, customer_created) |
triggers[].schedule | string | - | Cron-Ausdruck (z. B. 0 9 * * * für täglich 9 Uhr) |
triggers[].webhook | string | - | Webhook-Pfad (z. B. /agents/cart-recovery/trigger) |
triggers[].conditions | array | [] | Filterbedingungen für den Trigger |
triggers[].debounce | string | - | Debounce-Fenster (z. B. 5m, 1h) |
Berechtigungsfelder
| Feld | Typ | Standard | Beschreibung |
|---|---|---|---|
permissions | array | [] | Erforderliche Berechtigungsbereiche für Prüfprotokoll |
related_agents | array | [] | Agent-IDs, an die dieser Agent delegieren kann |
escalation | string | - | Wohin geroutet wird, wenn der Agent unsicher ist (human, supervisor-agent) |
Tools: Zuordnung zu Brevo MCP-Servern
Das tools-Feld referenziert Brevo MCP-Server-Modulnamen. Jedes Modul entspricht einem bestimmten Endpunkt auf 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
Verwenden Sie die minimale Menge an Tools, die Ihr Agent benötigt. Weniger Tools = besseres KI-Reasoning und schnellere Antworten. Alle verfügbaren Module finden Sie unter Brevo MCP-Server.
Trigger
Event-Trigger
Den Agent aktivieren, wenn etwas in Ihrem System passiert:
triggers: - event: cart_abandoned conditions: - cart_value: "> 50" - items_count: ">= 1" - time_since_activity: "> 30m" debounce: 5mZeitplan-Trigger
Den Agent nach einem wiederkehrenden Zeitplan ausführen:
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 monthWebhook-Trigger
Den Agent per HTTP aufrufen:
triggers: - webhook: /agents/win-back/trigger method: POST authentication: api_keyMarkdown-Textkörper: Anweisungen
Der Textkörper der Agent-Spezifikation sind natürlichsprachige Anweisungen. Schreiben Sie ihn, als würden Sie einen erfahrenen Marketer briefen:
Struktur
# 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.Effektive Anweisungen schreiben
Konkret über die Strategie sein, nicht nur über Ziele:
## 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 sequenceLeitplanken explizit definieren:
## 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 reviewMulti-Agent-Ketten
Für komplexe Workflows mehrere Agents in einer Kette kombinieren. Jeder Agent übernimmt eine Phase und gibt den Kontext weiter:
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.Ketten-Variablen
| Variable | Beschreibung |
|---|---|
{task} | Das ursprüngliche Ziel/die Anfrage |
{previous} | Ausgabe des vorherigen Schritts |
{step_N} | Ausgabe von Schritt N (0-indiziert) |
{artifacts_dir} | Verzeichnis für Dateiausgaben |
Vorgefertigte Agent-Spezifikationen
Kampagnen-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 campaignKunden-Intelligenz-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 weekBereitstellung
Agent programmatisch ausführen
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 trackedÜber Claude Code ausführen
# 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"Mit Cron planen
# 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>&1Nächste Schritte
- Brevo MCP-Server, Verfügbare Tools und Server-Konfiguration
- Ihren ersten Agent erstellen, Praxisanleitung
- Skills-Referenz, Tajo-Skills, die mit Agents kombiniert werden
- MCP-Architekturübersicht, Wie alles zusammenpasst