Agent skill

Cxas Dfcx Migration

by GoogleCloudPlatform in GoogleCloudPlatform/cxas-scrapi

Migrate Dialogflow CX (DFCX) agents to CXAS (Customer Experience Agent Studio) agents.

Apache-2.0Auto-check passedDevelopment

Install Cxas Dfcx Migration

skills CLI
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-dfcx-migration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-dfcx-migration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/cxas-dfcx-migration .claude/skills/cxas-dfcx-migration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cxas-dfcx-migration
GitHub stars
106
Token cost
~3.2k tokens
SKILL.md length
1,014 words
Files
10 (incl. scripts, references)
Skills in repo
14
Repo updated
First seen
Licence
Apache-2.0

At a glance

Migrate Dialogflow CX (DFCX) agents to CXAS (Customer Experience Agent Studio) agents.

  • Works in 4 steps: GCP project ID (target — where the new… → Location — default us. Do NOT default to… → Source agent — DFCX agent ID (full… → …
  • The user mentions DFCX migration
  • SKILL.md covers When to use this skill vs. the…, Prerequisites, Driving the flow interactively… and Quick Reference, plus 5 more sections
  • Runs Python scripts from its folder; calls python, pip and gcloud; reaches ces.cloud.google.com

What it does

Cxas Dfcx Migration is an agent skill from GoogleCloudPlatform/cxas-scrapi. 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), stage1.py (variable dedup + consolidation), stage2.py (instruction state machines + tool mocks + lint + report), stage3.py (rewires consolidated topology from source dep graph; only needed when stage1…

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts and reference files (for example `references/migration-options.md`, `scripts/_prompts.py` and `scripts/_shared.py`).

It sits in Development, covering Linting and formatting. The repository describes itself as: A powerful Python API, CLI, and set of Agent Skills for CX Agent Studio to automate, evaluate, and scale your agents with ease. The licence is Apache-2.0.

When your agent uses it

  • The user mentions DFCX migration
  • Migrating agents
  • Converting DFCX to CXAS
  • Agent migration

Example prompts

  • “/cxas-dfcx-migration”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. GCP project ID (target — where the new CXAS app will live).
  2. Location — default us. Do NOT default to global — it does not work for CXAS apps in most projects.
  3. Source agent — DFCX agent ID (full resource name) or path to a local .zip export.
  4. Target name — display name for the new CXAS app.

What it can do on your machine

Read from SKILL.md and the folder at commit ffba639. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 8 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • pip
    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • ces.cloud.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cxas Dfcx Migration loads about 3.2k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 166 tokens; SKILL.md has 1,014 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~166
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from GoogleCloudPlatform/cxas-scrapi at commit ffba639, republished under its Apache-2.0 licence (© GoogleCloudPlatform). 1,014 words, ~3,154 tokens.

Download SKILL.mdSave it as .claude/skills/cxas-dfcx-migration/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
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:

ScriptWhat it doesRuntimeOutput
migrate.py1:1 conversion of every selected playbook/flow into the IR, and deploys base resources only (app, variables, tools). Agent deployment is DEFERRED to stage_1.py so large sources don't exceed the CXAS 100-agent cap — the compiled agents are saved in <target>_ir.json, not pushed. Pass --no-consolidate to push the full 1:1 agent set immediately (only safe below ~100 agents).~30 min for ~40 flows<target>_ir.json, <target>_migration_report.md, <target>_unit_tests.json
stage_1.pyLoads the IR bundle, runs CXASOptimizer.optimize_stage1 (variable dedup) and Gemini structural consolidation (N→M agent grouping). This is the first agent push to CXAS — only the consolidated (N→M) agents are deployed; the raw 1:1 originals are never pushed (consolidate() drops them and the pre-consolidation snapshot is used transiently for the integrity check only, never persisted). CXAS Version 0.0.2 (dedup) and 0.0.3 (consolidation).~15 minUpdated <target>_ir.json, <target>_grouping.json
stage_2.pyLoads 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 minUpdated <target>_ir.json, <target>_optimization_report.md, regenerated <target>_unit_tests.json
stage_3.pyOnly 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 secUpdated <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:

bash
# Same E2E plumbing, non-interactive (standard optimized profile by default):
cxas migrate dfcx --run --source-agent-id … --project-id … --target-name …

# Non-interactive Stage Checkpoint optimization runs:
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  # interactive stage picker

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

bash
# Ensure cxas_scrapi is installed editable (so this skill picks up local changes)
pip install -e .

# Auth
gcloud auth application-default login
gcloud auth list   # confirm the account has read on source + admin on target

InquirerPy is required for the interactive prompts (matches the agent-foundry skill):

bash
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:

  1. GCP project ID (target — where the new CXAS app will live).
  2. Location — default us. Do NOT default to global — it does not work for CXAS apps in most projects.
  3. Source agent — DFCX agent ID (full resource name) or path to a local .zip export.
  4. 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

bash
# 1:1 migration (interactive — InquirerPy will prompt for project + location)
python .agents/skills/cxas-dfcx-migration/scripts/migrate.py

# Fully scripted
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

# Pre-flight HTML preview only (no migration)
python .agents/skills/cxas-dfcx-migration/scripts/migrate.py \
  --source-agent-id "<id>" --project-id <proj> --target-name preview_only \
  --preview-only --yes

# Stage 1 — variable dedup + Gemini consolidation
python .agents/skills/cxas-dfcx-migration/scripts/stage_1.py --target-name my_cxas_app

# Stage 1 — replay a saved grouping JSON
python .agents/skills/cxas-dfcx-migration/scripts/stage_1.py \
  --target-name my_cxas_app --grouping-json my_cxas_app_grouping.json --yes

# Stage 2 — instruction state machines + tool mocks + lint + report
python .agents/skills/cxas-dfcx-migration/scripts/stage_2.py --target-name my_cxas_app

# Stage 3 — rewire consolidated agent parent-child topology (idempotent)
python .agents/skills/cxas-dfcx-migration/scripts/stage_3.py --target-name my_cxas_app --architecture hub-and-spoke
Show full SKILL.md (540 more words)Show less

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).

Operationsrc/ entry point
Source agent fetch / zip parsemigration/dfcx_exporter.py:ConversationalAgentsAPI
1:1 migrationmigration/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 conveniencemigration/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 synthesismigration/structural_consolidator.py:StructuralConsolidator
Pre-deploy integrity checksmigration/integrity_checks.py:check_consolidation_integrity
Parent-child topology + orphan cleanupmigration/topology_wirer.py
Update-pass redeploysmigration/service.py:MigrationService._deploy_base_resources(is_update_pass=True) + _deploy_pending_agents(is_update_pass=True)
Topology linkmigration/cxas_topology_linker.py
Version checkpointscore/versions.py:Versions.create_version
Topology SVGmigration/graph_visualizer.py:HighLevelGraphVisualizer
Per-resource Rich treesmigration/playbook_visualizer.py + migration/flow_visualizer.py
Deterministic unit testsmigration/eval_generator.py:DeterministicEvalGenerator
Migration reportmigration/dfcx_migration_reporter.py
Optimization audit reportmigration/optimization_reporter.py:OptimizationReporter
Grouping review TUI (accept / re-propose / merge / split / rename)cli/grouping_review.py:interactive_review
HTML pre-flight previewmigration/html_preview.py
Post-deploy lintermigration/post_deploy_lint.py
IR bundle persistencemigration/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:

jsonc
{
  "schema_version": "1",
  "created_at": "2026-05-14T15:30:00",
  "config": { /* MigrationConfig */ },
  "source_agent_data": { /* DFCXAgentIR — needed for tool-mock context */ },
  "ir": { /* MigrationIR — mutated by each stage */ },
  "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": { /* present if Stage 1 ran consolidation */ }
}

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.

© GoogleCloudPlatform, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references) in .agents/skills/cxas-dfcx-migration of GoogleCloudPlatform/cxas-scrapi.

  • SKILL.md
  • references/migration-options.md
  • scripts/_prompts.py
  • scripts/_shared.py
  • scripts/convert_dfcx_tests.py
  • scripts/migrate.py
  • scripts/run_simulations.py
  • scripts/stage_1.py
  • scripts/stage_2.py
  • scripts/stage_3.py

Open the folder on GitHubat commit ffba639

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Categories

Questions about Cxas Dfcx Migration

What does Cxas Dfcx Migration do?

Migrate Dialogflow CX (DFCX) agents to CXAS (Customer Experience Agent Studio) agents. Cxas Dfcx Migration is an agent skill from GoogleCloudPlatform/cxas-scrapi. Migrate Dialogflow CX (DFCX) agents to CXAS (Customer Experience Agent Studio) agents.

When should I use Cxas Dfcx Migration?

Cxas Dfcx Migration fits situations like: the user mentions DFCX migration; migrating agents; converting DFCX to CXAS; agent migration.

How do I install Cxas Dfcx Migration in Claude Code?

Run `npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-dfcx-migration -a claude-code`. Or copy the skill folder (.agents/skills/cxas-dfcx-migration in GoogleCloudPlatform/cxas-scrapi) into .claude/skills/cxas-dfcx-migration in your project. Claude Code loads it when a task matches its description.

How do I install Cxas Dfcx Migration in Codex?

Run `npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-dfcx-migration -a codex`. Or copy the skill folder (.agents/skills/cxas-dfcx-migration in GoogleCloudPlatform/cxas-scrapi) into .agents/skills/cxas-dfcx-migration in your project. Codex loads it when a task matches its description.

Can I use Cxas Dfcx Migration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-dfcx-migration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cxas-dfcx-migration, .gemini/skills/cxas-dfcx-migration, .github/skills/cxas-dfcx-migration and .opencode/skills/cxas-dfcx-migration in your project.

What does Cxas Dfcx Migration need to run?

Going by SKILL.md and its folder, Cxas Dfcx Migration needs Python for the scripts in its folder and the command-line tools its instructions call (python, pip and gcloud). Our summary lists: Python 3.

Does Cxas Dfcx Migration access the network?

SKILL.md names 1 domain. In commands or code: ces.cloud.google.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Cxas Dfcx Migration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cxas Dfcx Migration use?

Cxas Dfcx Migration is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cxas Dfcx Migration use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.2k tokens, read only when the agent opens those files.

What are the alternatives to Cxas Dfcx Migration?

Skills that share tags, products or a category with Cxas Dfcx Migration: Install Anti-Slop Oxlint Rules (dmmulroy/anti-slop, 5.2k stars), Babysit PR To Pass CI (sgl-project/sglang, 37k stars), Rust Best Practices (farm-fe/farm, 5.6k stars) and Go Pedantry (chromedp/chromedp, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cxas Dfcx Migration?

GoogleCloudPlatform (a GitHub organization) maintains it in GoogleCloudPlatform/cxas-scrapi, which has 106 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 6, 2026.

Source: GoogleCloudPlatform/cxas-scrapi on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.