Quality Flywheel
GoogleCloudPlatform/vertex-ai-samples
Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK.
Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases.
Install Cxas Sim Eval
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-eval --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .claude/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.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/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .claude/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-evalType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-eval --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .agents/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .agents/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-eval --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .cursor/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .cursor/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/GoogleCloudPlatform/cxas-scrapi.git --path .agents/skills/cxas-sim-eval--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-eval --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .gemini/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .gemini/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-evalInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .github/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .github/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install GoogleCloudPlatform/cxas-scrapi cxas-sim-eval --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GoogleCloudPlatform/cxas-scrapi.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/cxas-sim-eval .opencode/skills/cxas-sim-eval && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cxas-sim-eval" agent skill from https://github.com/GoogleCloudPlatform/cxas-scrapi/tree/main/.agents/skills/cxas-sim-eval into .opencode/skills/cxas-sim-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cxas-sim-eval", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
cxas-sim-eval- GitHub stars
- 106
- Token cost
- ~1.2k tokens
- SKILL.md length
- 466 words
- Files
- 5 (incl. scripts)
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases.
- Works in 10 steps: Check Environment → Get App Name and Output Directory → Fetch Evaluations → …
- Generating high-level
- SKILL.md covers Steps, Automation Scripts and Interpreting Cognitive…
- Runs Python scripts from its folder; calls python and gcloud
What it does
Cxas Sim Eval is an agent skill from GoogleCloudPlatform/cxas-scrapi. 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.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `scripts/convert_eval.py`, `scripts/fetch_app_data.py` and `scripts/fetch_tool_schemas.py`).
It sits in Testing & QA, covering Test generation. It works with Google Cloud. 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
- Generating high-level
- Goal-oriented test cases from turn-by-turn evaluation JSONs
- When enriching test expectations with inferred tool calls
Example prompts
- “Use the cxas-sim-eval skill to convert CXAS golden evaluations to SCRAPI SimulationEvals test cases”
- “/cxas-sim-eval”
Requirements
- Python 3
Workflow steps
10 steps, taken from the step headings in SKILL.md.
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 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythongcloud
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use gcloud, which can reach the network depending on how they are called.
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 Sim Eval loads about 1.2k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 466 words of instructions outside code blocks.
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). 466 words, ~1,184 tokens.
Download SKILL.mdSave it as
.claude/skills/cxas-sim-eval/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- cxas-sim-eval
- description
- 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.
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 listIf needed, login with:
gcloud auth login2. 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_directory2. Fetch Tool Schemas
scripts/fetch_tool_schemas.py
Fetches the full schemas for all tools available in the app.
Usage:
python .agents/skills/cxas-sim-eval/scripts/fetch_tool_schemas.py \
--app-name "projects/.../locations/.../apps/..." \
--output-dir /path/to/output_directory3. Convert Evaluations
scripts/convert_eval.py
Converts the fetched evaluations to simulation test cases, using the fetched tool schemas to infer expectations.
Usage:
python .agents/skills/cxas-sim-eval/scripts/convert_eval.py \
--output-dir /path/to/output_directory \
--parallelism 5Show full SKILL.md (203 more words)Show less
4. Run Evaluations
scripts/run_evals.py
Runs the simulation evaluations, logs raw results, and generates a combined HTML report.
Cognitive Diagnostics Analysis:
If the agent has the intercept_and_score_reasoning tool enabled, this script will automatically extract and analyze the agent's internal monologue for failed evaluations. It detects issues like overthinking, hesitation, and backtracking. Furthermore, it correlates these diagnostics with the agent's instructions to generate actionable suggestions for improvement directly in the HTML report.
Usage:
python .agents/skills/cxas-sim-eval/scripts/run_evals.py \
--app-name "projects/.../locations/.../apps/..." \
--output-dir /path/to/output_directory \
--parallelism 5 \
--start-index 0 \
--end-index 10Interpreting Cognitive Diagnostics
When running evaluations with the intercept_and_score_reasoning tool enabled, the system extracts diagnostics to help you identify issues in agent reasoning.
Key Signals
Overthinking (Verbosity)
- Symptom: Internal monologue exceeds 350 or 600 characters.
- Meaning: The agent is struggling to process complex or circular instructions.
- Fix: Simplify instructions. Break down complex tasks into smaller, linear steps.
Hedging
- Symptom: Use of words like "might be", "guess", "unsure", "assume".
- Meaning: The agent is uncertain about its next action, often due to missing edge case handling.
- Fix: Add explicit instructions for the scenario the agent is unsure about.
Backtracking
- Symptom: Use of words like "wait", "actually", "on second thought".
- Meaning: The agent is abandoning a plan mid-turn or correcting itself, indicating unclear triggers.
- Fix: Clarify triggers and state transitions in instructions.
© 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 4 other files (scripts) in .agents/skills/cxas-sim-eval of GoogleCloudPlatform/cxas-scrapi.
- SKILL.md
- scripts/convert_eval.py
- scripts/fetch_app_data.py
- scripts/fetch_tool_schemas.py
- scripts/run_evals.py
Open the folder on GitHubat commit ffba639
Compare with similar skills
Cxas Sim Eval next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cxas Sim Eval this skillGoogleCloudPlatform/cxas-scrapi | 106 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Quality FlywheelGoogleCloudPlatform/vertex-ai-samples | 791 | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Ak Dev New Secret Provideryaalalabs/agent-kernel | 191 | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Write and Verify Playwright Testsappsmithorg/appsmith | 41k | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | |
| Adk Verify Snippetsgoogle/adk-python | 22k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Engine E2Ewix/react-native-navigation | 13k | — | ~1.1k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Cxas Sim Eval
What does Cxas Sim Eval do?
Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases. Cxas Sim Eval is an agent skill from GoogleCloudPlatform/cxas-scrapi. Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases.
When should I use Cxas Sim Eval?
Cxas Sim Eval fits situations like: generating high-level; goal-oriented test cases from turn-by-turn evaluation JSONs; when enriching test expectations with inferred tool calls.
How do I install Cxas Sim Eval in Claude Code?
Run `npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a claude-code`. Or copy the skill folder (.agents/skills/cxas-sim-eval in GoogleCloudPlatform/cxas-scrapi) into .claude/skills/cxas-sim-eval in your project. Claude Code loads it when a task matches its description.
How do I install Cxas Sim Eval in Codex?
Run `npx skills add GoogleCloudPlatform/cxas-scrapi --skill cxas-sim-eval -a codex`. Or copy the skill folder (.agents/skills/cxas-sim-eval in GoogleCloudPlatform/cxas-scrapi) into .agents/skills/cxas-sim-eval in your project. Codex loads it when a task matches its description.
Can I use Cxas Sim Eval 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-sim-eval -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-sim-eval, .gemini/skills/cxas-sim-eval, .github/skills/cxas-sim-eval and .opencode/skills/cxas-sim-eval in your project.
What does Cxas Sim Eval need to run?
Going by SKILL.md and its folder, Cxas Sim Eval needs Python for the scripts in its folder and the command-line tools its instructions call (python and gcloud). Our summary lists: Python 3.
Does Cxas Sim Eval access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Cxas Sim Eval 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 Sim Eval use?
Cxas Sim Eval 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 Sim Eval use?
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Cxas Sim Eval?
Skills that share tags, products or a category with Cxas Sim Eval: Quality Flywheel (GoogleCloudPlatform/vertex-ai-samples, 791 stars), Ak Dev New Secret Provider (yaalalabs/agent-kernel, 191 stars), Write and Verify Playwright Tests (appsmithorg/appsmith, 41k stars) and Adk Verify Snippets (google/adk-python, 22k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cxas Sim Eval?
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.