What This Skill Does

Migrates a Dialogflow CX v3beta1 agent to Google Customer Engagement Suite (CES) Conversational Agents format, producing:

Output File	Contents
ces_agent.json	CES agent definition (importable via Console or REST API)
golden_evals.csv	CES batch evaluation CSV (golden test cases)
entity_types.json	Entity type definitions for manual re-creation
migration_report.md	Full migration summary with next steps

Migration Mapping

Dialogflow CX	→	CES Conversational Agents
Agent	→	Agent Application + Root Agent
Flow (non-default)	→	Sub-Agent
Pages + Routes	→	Agent Instructions (natural language)
Intent training phrases	→	Root agent routing hints
Entity Types	→	Exported JSON (manual import)
Webhook	→	Tool (OpenAPI schema)
Form Parameters	→	Instruction slot-filling steps
Test Cases	→	Golden Evaluations CSV

Prerequisites

• GCP Auth: gcloud auth application-default login
• Project access: Dialogflow CX API enabled on the project
• Python: 3.10+
• Packages: pip install google-cloud-dialogflow-cx google-auth

Usage

Run Migration

python migrate.py \
  --project YOUR_PROJECT_ID \
  --agent-id YOUR_AGENT_UUID \
  --output ./migration_output

Dry Run (fetch + preview, no files written)

python migrate.py \
  --project YOUR_PROJECT_ID \
  --agent-id YOUR_AGENT_UUID \
  --dry-run

Custom location (non-global agents)

python migrate.py \
  --project YOUR_PROJECT_ID \
  --agent-id YOUR_AGENT_UUID \
  --location us-central1 \
  --output ./migration_output

Example (carconnect agent)

python migrate.py \
  --project genaiguruyoutube \
  --agent-id 3736c564-5b3b-4f93-bbb2-367e7f04e4e8 \
  --output ./carconnect_ces

Expected output:

• 14 flows → 13 sub-agents + root agent enrichment
• 31 intents → root routing hints
• 5 entity types → exported JSON
• 2 webhooks → 2 OpenAPI tools
• Test cases → golden_evals.csv

Post-Migration Steps

• Review ces_agent.json — check sub-agent instructions make sense, update tool endpoints
• Import into CES Console:

- Go to ces.cloud.google.com - Select project → Import Agent → Upload ces_agent.json

• Upload Golden Evals:

- Evaluate tab → + Add test case → Golden → Upload file → select golden_evals.csv

• Re-create Entity Types from entity_types.json (CES uses them as tool parameters)
• Update webhook endpoints in the Tools section of your CES agent
• Run evaluation suite → review pass rates → iterate on instructions

Retry Logic

All Google API calls use exponential backoff (up to 4 attempts, base delay 1.5s × 2ⁿ). If the API is rate-limited or temporarily unavailable, the tool retries automatically.

Limitations & Known Gaps

• Rich response types (carousels, chips, images) are converted to text messages. Update manually in CES.
• Conditional routes using session parameter syntax ($session.params.X) are preserved as-is in instructions but may need updating for CES parameter syntax.
• DTMF / telephony settings are not migrated (CES has different telephony config).
• Entity type import: CES does not have a direct batch import API for entity types — use the exported JSON as reference to create them manually or via REST.
• Webhook auth: OAuth and mTLS configs are noted but credentials must be re-configured in CES.

Autoresearch Evals (binary pass/fail)

When running autoresearch on this skill, use these evals:

• EVAL_FLOWS: All non-default flows appear as sub-agents in ces_agent.json?
• EVAL_TOOLS: All webhooks appear as tools with OpenAPI schemas in ces_agent.json?
• EVAL_ENTITIES: All entity types exported to entity_types.json?
• EVAL_EVALS_CSV: golden_evals.csv has correct header + at least one golden eval row?
• EVAL_INSTRUCTIONS: Each sub-agent has non-empty instructions?
• EVAL_REPORT: migration_report.md exists and contains a stats table?