Beantrage frühzeitigen Zugang

Gib deinen Vornamen und eine E-Mail-Adresse oder Telefonnummer an. Wir melden uns mit den Details zum Tajo-Zugang bei dir.

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-name
description: What this agent does (max 160 chars)
version: 1.0.0
temperature: 0.2
max_tokens: 4096
tools:
- brevo_contacts
- brevo_email_campaign_management
- brevo_sms_campaigns
triggers:
- 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

FeldTypBeschreibung
namestringEindeutiger Bezeichner in kebab-case (z. B. cart-recovery-agent)
descriptionstringWas dieser Agent tut (max. 160 Zeichen)
versionstringSemantische Version (z. B. 1.0.0)
toolsarrayBrevo MCP-Server-Module, auf die dieser Agent zugreifen kann

Verhaltensfelder

FeldTypStandardBeschreibung
temperaturefloat0.3LLM-Temperatur. Niedriger = deterministischer. 0.1-0.2 für Datenoperationen, 0.3-0.5 für Kampagnenentwurf
max_tokensinteger4096Maximale Antwortlänge pro Runde
modelstringclaude-sonnet-4-6Zu verwendendes LLM-Modell

Trigger-Felder

FeldTypStandardBeschreibung
triggersarray[]Events, Zeitpläne oder Webhooks, die diesen Agent aktivieren
triggers[].eventstring-Event-Name (z. B. cart_abandoned, customer_created)
triggers[].schedulestring-Cron-Ausdruck (z. B. 0 9 * * * für täglich 9 Uhr)
triggers[].webhookstring-Webhook-Pfad (z. B. /agents/cart-recovery/trigger)
triggers[].conditionsarray[]Filterbedingungen für den Trigger
triggers[].debouncestring-Debounce-Fenster (z. B. 5m, 1h)

Berechtigungsfelder

FeldTypStandardBeschreibung
permissionsarray[]Erforderliche Berechtigungsbereiche für Prüfprotokoll
related_agentsarray[]Agent-IDs, an die dieser Agent delegieren kann
escalationstring-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/mcp

Tip

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: 5m

Zeitplan-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 month

Webhook-Trigger

Den Agent per HTTP aufrufen:

triggers:
- webhook: /agents/win-back/trigger
method: POST
authentication: api_key

Markdown-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:

## Bad
Re-engage churned customers.
## Good
When a customer hasn't purchased in 90+ days:
1. Check their last 3 orders for product category preferences
2. Create a personalized discount based on AOV (10% if AOV > $100, 15% if < $100)
3. Send email with subject line referencing their preferred category
4. Wait 72 hours, if no open, send SMS with discount code
5. Wait 7 days, if no purchase, mark as deep-churn and stop sequence

Leitplanken 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 review

Multi-Agent-Ketten

Für komplexe Workflows mehrere Agents in einer Kette kombinieren. Jeder Agent übernimmt eine Phase und gibt den Kontext weiter:

chain.yaml
name: quarterly-retention-campaign
steps:
- 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

VariableBeschreibung
{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-orchestrator
description: Design and execute multi-channel campaigns from natural language prompts
version: 2.0.0
temperature: 0.3
tools:
- brevo_contacts
- brevo_segments
- brevo_email_campaign_management
- brevo_templates
- brevo_sms_campaigns
- brevo_whatsapp_campaigns
- brevo_campaign_analytics
triggers:
- webhook: /agents/campaign/trigger
method: POST
---
# Campaign Orchestrator
You are a multi-channel marketing campaign specialist.
Given a campaign brief, you design, build, and launch
campaigns across email, SMS, and WhatsApp via Brevo.
## Process
1. Parse the campaign brief (audience, message, goal, timeline)
2. Create or identify the target segment in Brevo
3. Select the best channel(s) based on audience preference data
4. Build campaign content using existing templates or creating new ones
5. Configure send schedule and A/B tests
6. 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 campaign

Kunden-Intelligenz-Agent

---
name: customer-intelligence
description: Autonomous segmentation, RFM scoring, and churn prediction
version: 1.5.0
temperature: 0.2
tools:
- brevo_contacts
- brevo_segments
- brevo_attributes
- brevo_lists
- brevo_campaign_analytics
triggers:
- schedule: "0 6 * * MON"
timezone: "UTC"
---
# Customer Intelligence Agent
You analyze customer data in Brevo to generate actionable
segments and insights for marketing teams.
## Weekly Analysis
1. Pull contact activity data from campaign analytics
2. 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
## Output
Produce 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 week

Bereitstellung

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 trail
console.log(result.metrics); // Events tracked

Über Claude Code ausführen

Terminal window
# Point to your agent spec and let Claude execute it
claude "Run the agent defined in ./agents/cart-recovery-agent.md for today's abandoned carts"

Mit Cron planen

Terminal window
# Run the customer intelligence agent every Monday at 6am
0 6 * * MON claude --print "Run ./agents/customer-intelligence.md weekly analysis" >> /var/log/tajo-agents.log 2>&1

Nächste Schritte

Beantrage frühzeitigen Zugang

Gib deinen Vornamen und eine E-Mail-Adresse oder Telefonnummer an. Wir melden uns mit den Details zum Tajo-Zugang bei dir.

automatische Erkennung
AI-Assistent

Hallo! Fragen Sie mich alles über die Dokumentation.