| name | cxas-dfcx-migration |
| description | Migrate Dialogflow CX (DFCX) agents to CXAS (Customer Experience Agent Studio) agents. Use this skill when the user mentions DFCX migration, migrating agents, converting DFCX to CXAS, porting agents, agent migration, or post-migration optimization/consolidation. Four independently runnable scripts: migrate.py (1:1), stage_1.py (variable dedup + consolidation), stage_2.py (instruction state machines + tool mocks + lint + report), stage_3.py (rewires consolidated topology from source dep graph; only needed when stage_1 ran consolidation). State persists between scripts via <target>_ir.json so each can run / re-run / resume independently. |
DFCX to CXAS Migration
Four small scripts, one persistent IR bundle:
| Script | What it does | Runtime | Output |
|---|
migrate.py | 1:1 conversion of every selected playbook/flow into a CXAS agent. | ~30 min for ~40 flows | <target>_ir.json, <target>_migration_report.md, <target>_unit_tests.json |
stage_1.py | Loads the IR bundle, runs CXASOptimizer.optimize_stage1 (variable dedup) and Gemini structural consolidation (N→M agent grouping). Pushes via update-pass deploys. Deletes original orphans (iterative). CXAS Version 0.0.2 (dedup) and 0.0.3 (consolidation). | ~15 min | Updated <target>_ir.json (with pre_consolidation_ir snapshot for rollback), <target>_grouping.json |
stage_2.py | Loads the IR bundle, runs CXASOptimizer.optimize_stage2 (instruction state machines + tool mocks). Pushes via update-pass deploys. CXAS Version 0.0.4. Re-generates unit tests. Lints. Writes the audit report. | ~10 min | Updated <target>_ir.json, <target>_optimization_report.md, regenerated <target>_unit_tests.json |
stage_3.py | Only after Stage 1 consolidation. Rewires the consolidated agents' parent → children topology by mapping the SOURCE DFCX dep graph onto the new groups (rather than relying on what the synthesized PIF XML happened to reference) according to Spoke-Hub architecture style. Sets app root_agent to the is_root group. Idempotent — safe to re-run. CXAS Version 0.0.5. | ~10 sec | Updated <target>_ir.json stage history; CXAS app's child_agents set per group |
State flows through <target>_ir.json (a Pydantic IRBundle containing the MigrationConfig, source DFCXAgentIR, target MigrationIR, stage history, and version checkpoints). Each stage loads it from disk, mutates it, and writes it back. No re-fetching or re-compiling between stages.
When to use this skill vs. the CLI directly
This skill (InquirerPy prompts + HTML pre-flight preview + Gemini model picker) is the right entry when you want to interactively drive a migration with rich pre-flight context. The same MigrationService.run_stage* methods this skill calls are also exposed via the canonical CLI for scripted / CI use:
cxas migrate dfcx --run --source-agent-id … --project-id … --target-name …
cxas migrate dfcx --optimize --stage 1 --target-name my_app
cxas migrate dfcx --optimize --stage 2 --target-name my_app
cxas migrate dfcx --optimize --stage 3 --target-name my_app --architecture hub-and-spoke
cxas migrate dfcx --optimize --stage resume --target-name my_app
The skill, the dashboard, and the E2E / Checkpoint commands all go through the same MigrationService.run_stage_1/run_stage_2/run_stage_3 methods — pick whichever entry point matches your workflow.
Prerequisites
pip install -e .
gcloud auth application-default login
gcloud auth list
InquirerPy is required for the interactive prompts (matches the agent-foundry skill):
pip install InquirerPy
Driving the flow interactively (from Claude)
When invoked through Claude, lead the user through one question at a time. The scripts will prompt for missing inputs via InquirerPy, but you should pre-collect:
- GCP project ID (target — where the new CXAS app will live).
- Location — default
us. Do NOT default to global — it does not work for CXAS apps in most projects.
- Source agent — DFCX agent ID (full resource name) or path to a local
.zip export.
- Target name — display name for the new CXAS app.
Optional follow-ups: --env (PROD/AUTOPUSH), --model (Gemini), --migration-version (1.0/2.0).
Quick Reference
python .agents/skills/cxas-dfcx-migration/scripts/migrate.py
python .agents/skills/cxas-dfcx-migration/scripts/migrate.py \
--source-agent-id "projects/<src_proj>/locations/us/agents/<uuid>" \
--project-id <target_proj> --location us \
--target-name my_cxas_app --yes
python .agents/skills/cxas-dfcx-migration/scripts/migrate.py \
--source-agent-id "<id>" --project-id <proj> --target-name preview_only \
--preview-only --yes
python .agents/skills/cxas-dfcx-migration/scripts/stage_1.py --target-name my_cxas_app
python .agents/skills/cxas-dfcx-migration/scripts/stage_1.py \
--target-name my_cxas_app --grouping-json my_cxas_app_grouping.json --yes
python .agents/skills/cxas-dfcx-migration/scripts/stage_2.py --target-name my_cxas_app
python .agents/skills/cxas-dfcx-migration/scripts/stage_3.py --target-name my_cxas_app --architecture hub-and-spoke
What lives in the skill vs. in cxas_scrapi
The skill is a thin orchestrator. Every migration / optimization step lives in src/cxas_scrapi/migration/ and is reachable via MigrationService.run_stage_* methods, so the same logic powers all three entry points: this skill, cxas migrate dfcx (interactive TUI), and non-interactive command modes (--run / --optimize).
| Operation | src/ entry point |
|---|
| Source agent fetch / zip parse | migration/dfcx_exporter.py:ConversationalAgentsAPI |
| 1:1 migration | migration/service.py:MigrationService.run_migration |
| Stage 1 orchestrator (variable dedup + consolidation + integrity + topology link + orphan cleanup + versions + bundle persist) | migration/service.py:MigrationService.run_stage_1 |
| Stage 2 orchestrator (state machines + tool mocks + unit-test regen + lint + audit report + bundle persist) | migration/service.py:MigrationService.run_stage_2 |
| Stage 3 orchestrator (parent-child topology wiring) | migration/service.py:MigrationService.run_stage_3 |
| Bundle persist convenience | migration/service.py:MigrationService.persist_bundle |
| Variable dedup primitive (Stage 1) | migration/optimizer.py:CXASOptimizer.optimize_stage1 |
| Instruction restructuring + tool mocks primitive (Stage 2) | migration/optimizer.py:CXASOptimizer.optimize_stage2 |
| Gemini N→M grouping + per-group PIF XML synthesis | migration/structural_consolidator.py:StructuralConsolidator |
| Pre-deploy integrity checks | migration/integrity_checks.py:check_consolidation_integrity |
| Parent-child topology + orphan cleanup | migration/topology_wirer.py |
| Update-pass redeploys | migration/service.py:MigrationService._deploy_base_resources(is_update_pass=True) + _deploy_pending_agents(is_update_pass=True) |
| Topology link | migration/cxas_topology_linker.py |
| Version checkpoints | core/versions.py:Versions.create_version |
| Topology SVG | migration/graph_visualizer.py:HighLevelGraphVisualizer |
| Per-resource Rich trees | migration/playbook_visualizer.py + migration/flow_visualizer.py |
| Deterministic unit tests | migration/eval_generator.py:DeterministicEvalGenerator |
| Migration report | migration/dfcx_migration_reporter.py |
| Optimization audit report | migration/optimization_reporter.py:OptimizationReporter |
| Grouping review TUI (accept / re-propose / merge / split / rename) | cli/grouping_review.py:interactive_review |
| HTML pre-flight preview | migration/html_preview.py |
| Post-deploy linter | migration/post_deploy_lint.py |
| IR bundle persistence | migration/data_models.py:IRBundle |
Skill-local helpers (UX glue only — InquirerPy prompts + thin
delegations to MigrationCLI):
_prompts.py — InquirerPy prompt library (matches agent-foundry).
_shared.py — InquirerPy variants of project/location prompts, source loader, and MigrationConfig assembly; plus pure delegations to MigrationCLI for check_auth, run_dependency_analysis, select_resources, show_visualizations.
The stage scripts now import the promoted modules directly:
from cxas_scrapi.migration.data_models import IRBundle
(plus html_preview in migrate.py and phase_tracker) and call sites use the
canonical model names (IRBundle, phase_tracker.PhaseTracker,
html_preview.generate_html_report) — no re-export shim layer.
The skill's stage scripts (migrate.py / stage_1.py / stage_2.py / stage_3.py) are now ~80-200 line shells: parse args → restore service from bundle → call the matching MigrationService.run_stage_* → print summary. There is no orchestration logic left in the skill — only InquirerPy prompts and the HTML preview that's specific to the skill's pre-flight UX.HTML preview that's specific to the skill's pre-flight UX.
IR bundle (<target>_ir.json)
The unit of state shared across the three scripts. Pydantic IRBundle model:
{
"schema_version": "1",
"created_at": "2026-05-14T15:30:00",
"config": { },
"source_agent_data": { },
"ir": { },
"stage_history": [
{"phase": "migrate", "status": "ok", ...},
{"phase": "stage1", "status": "ok", ...}
],
"app_url": "https://ces.cloud.google.com/...",
"version_checkpoints": [["0.0.1", "Stage 1: ..."]],
"grouping": { }
}
Killing a stage script mid-run leaves the bundle untouched (only persisted on success). Re-running picks up where the last successful stage left off.
Pre-flight HTML preview
migrate.py generates <target>_tree_preview.html in ~5 seconds after source loading. Open it in any browser to see:
- Source overview (resource counts, estimated migration time).
- Topology graph (graphviz SVG when
dot is on PATH; Mermaid fallback otherwise).
- Per-playbook and per-flow Rich trees.
migrate.py --preview-only exits after the preview without running the migration.
Troubleshooting
create_app returns 404 / 501 / MethodNotImplemented — your --location is wrong. CXAS apps in most projects live in us, not global. Pass --location us.
AlreadyExists: App with same display name — pick a different --target-name. Old runs leave deployed apps behind even on partial failure.
- Stage 1 / Stage 2 fail with
No IR bundle found — run migrate.py first to produce <target>_ir.json, or pass --ir-bundle <path> explicitly.
- Synthesis (Stage 1 consolidation) hangs on Gemini — fixed with per-group
asyncio.wait_for(timeout=600s) in structural_consolidator.synthesize_instructions. Override via SYNTHESIS_TIMEOUT_S env var. Hung groups fall back to the concatenated instruction.
gemini-2.5-flash-001 not found during AI augment — the Gemini call uses locations/global for the model; sometimes that endpoint is project-restricted. The migration continues with empty AI descriptions. Pick a different --model if you need them.
Detailed reference
See references/migration-options.md for full parameter / flag descriptions and the IR bundle schema.