What is cxas-sim-eval?

A converter that turns detailed CX Agent Studio evaluation records into higher-level test cases for the SCRAPI SimulationEvals testing framework. It can use the agent's tool definitions when adding expected tool calls.

Use it to fetch evaluations and tool information, then create SimulationEvals test cases from CXAS golden evaluations.

It connects turn-by-turn evaluations with a simulation test format, so tests can describe goals rather than every conversation turn.

cxas-sim-eval — Skill for Claude Code and Codex by GoogleCloudPlatform

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval

Clone the repo

git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval/github.svg)](https://agentmods.dev/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval)

Your own site

<a href="https://agentmods.dev/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,095 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00050	$0.01095
Opus 5.5	$0.00020	$0.00438
Sonnet 5.5	$0.00010	$0.00219
Haiku 4.5	$0.00005	$0.00110

Measured 1mo ago against content hash ac873c7c9457, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cxas-sim-eval scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/convert_eval.py, scripts/fetch_app_data.py, scripts/fetch_tool_schemas.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/cxas-sim-eval/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CXAS Evaluation to Simulation Converter

This skill helps convert turn-by-turn CXAS golden evaluations into high-level, goal-oriented test cases for the SCRAPI SimulationEvals framework. It analyzes the agent's tools to enrich expectations with specific tool calls.

Steps

1. Check Environment

Ensure cxas_scrapi is installed as a python package. You can check this by running:

python -c "import cxas_scrapi"

Ensure gcloud is authenticated properly:

gcloud auth list

If needed, login with:

gcloud auth login

2. Get App Name and Output Directory

[!IMPORTANT] You MUST ask the user for the full resource name of the app/agent (e.g., projects/.../locations/.../apps/...) and the base output directory before proceeding with any execution steps.

Ask the user for these values.

3. Fetch Evaluations

Fetch the list of evaluations using the CES API. Save each evaluation as a JSON file named after its display name under [output_dir]/golden_evals/.

4. Fetch Tool Schemas

Fetch the full schemas for all tools available in the app and save them under [output_dir]/tools/.

5. Fetch Agent Tools Configuration

Fetch the list of tools and toolsets used by the agent and save the configuration (e.g., to [output_dir]/agent_tools.json).

6. Convert Evaluations

Run the conversion script (convert_eval.py) to process the fetched evaluations and save the converted test cases under [output_dir]/sim_evals/.

Automation Scripts

Three scripts are available to automate the process:

1. Fetch Evaluations and Agent Config

scripts/fetch_app_data.py

Fetches evaluations and the list of tools used by the agent from the CES API.

Usage:

python .agents/skills/cxas-sim-eval/scripts/fetch_app_data.py \
  --app-name "projects/.../locations/.../apps/..." \
  --output-dir /path/to/output_directory

2. Fetch Tool Schemas

Read the full file on GitHub · 149 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 149 lines · 50 tokens per session scan A ac873c7c9457

Subscribe to this mod's changes

cxas-sim-eval is a skill published in the GitHub repository GoogleCloudPlatform/cxas-scrapi (110 stars, last pushed 2d ago), licensed Apache-2.0. It adds 50 tokens to every session and 1,095 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Testing

research-engineer

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apache/tika · 50 tokens

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davidondrej/skills · 68 tokens

cxas-sim-eval