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Extracts conversational transcripts from Cyara XML test case files.
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Basierend auf der SOC-Berufsklassifikation
End-to-end GECX/CXAS/CES conversational agent lifecycle -- build agents from requirements (PRD-to-agent), create and run evals (goldens, simulations, tool tests, callback tests), debug failures, and iterate to production quality. Use this skill whenever the user mentions GECX, CXAS, CES, SCRAPI, conversational agents, voice agents, audio agents, agent evals, pushing/pulling/linting agents, or agent instructions/callbacks/tools on the Google Customer Engagement Suite platform.
Automates the ingestion of customer requirement documents such as diagrams, BRDs, code etc., synthesizes high-fidelity natural transcripts, and compiles them into highly interactive, responsive Critical User Journey (CUJ) reports.
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.
Parsing and ingestion directives for the Python-based Agent Development Kit (ADK) conversational agent framework.
Parsing and Ingestion directives for the Dialogflow CX (DFCX) agent structure.
Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases. Use when generating high-level, goal-oriented test cases from turn-by-turn evaluation JSONs, and when enriching test expectations with inferred tool calls.
| name | cxas-cyara-ingestor |
| description | Extracts conversational transcripts from Cyara XML test case files. |
Use this skill when you need to extract dialogue turns and conversation flows from Cyara XML test case files.
Cyara files are XML documents containing test scenarios for voice or chat agents. They are rich sources for transcripts because they map user utterances to agent states.
expected_flow sequence, which
describes the chronological steps of the interaction.expected_flow.(User: ...) annotations. This directly
maps what the user said at that specific point in the flow.Greeting_State, Ask_Identifier) indicate the
Agent's state or prompt. You must infer natural Agent dialogue based on
these state names if literal text is not provided.end_session tool
call) rules.A summarized Cyara item might look like this: `yaml id: test_case_identifier utterances:
You should infer a transcript like: