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.
npx agentmods add skills/googlecloudplatform/cxas-scrapi/cxas-sim-evalnpx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-evalgit clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapiWrote 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.
[](https://agentmods.dev/skills/googlecloudplatform/cxas-scrapi/cxas-sim-eval)<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="Measured on agentmods" height="20"></a>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 | $0.00025 | $0.00548 |
| Sonnet 5 | $0.00010 | $0.00219 |
| Haiku 4.5 | $0.00005 | $0.00110 |
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 6d ago.
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.
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
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.
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.
- 6d ago First seen · 149 lines · 50 tokens per session scan A ac873c7c9457
cxas-sim-eval is a skill published in the GitHub repository GoogleCloudPlatform/cxas-scrapi (95 stars, last pushed 2d ago), licensed Apache-2.0. It adds 50 tokens to every session and 1,095 once invoked, about $0.0003 per session on Opus 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.
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