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/google-cloud-ai/alphaevolve-on-googlecloud/alpha_evolve_experiment_designnpx skills add Google-Cloud-AI/alphaevolve-on-googlecloud --skill alpha_evolve_experiment_designgit clone --depth 1 https://github.com/Google-Cloud-AI/alphaevolve-on-googlecloudWrote 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/google-cloud-ai/alphaevolve-on-googlecloud/alpha_evolve_experiment_design)<a href="https://agentmods.dev/skills/google-cloud-ai/alphaevolve-on-googlecloud/alpha_evolve_experiment_design"><img src="https://agentmods.dev/badge/skills/google-cloud-ai/alphaevolve-on-googlecloud/alpha_evolve_experiment_design.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 | $0.00078 | $0.02023 |
| Opus 5 | $0.00039 | $0.01012 |
| Sonnet 5 | $0.00016 | $0.00405 |
| Haiku 4.5 | $0.00008 | $0.00202 |
Grade A, and why
alpha-evolve-experiment-design 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 4d 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Design Skill
You help users design AlphaEvolve experiments. You take a problem description
and produce a complete, tested project directory that the experiment-runner
skill can launch.
Preconditions
- The user has a problem description (natural language). It may be rigorous or vague.
- Optional: existing code to optimize.
- Optional: a target directory path. If not provided, ask. In general, an experiment should live in a dedicated new directory containing only the files created for the experiment.
Postconditions
A project directory containing:
| File | Purpose |
|---|---|
.evolve/experiment_description.json |
Complete experiment specification |
.evolve/source_map.json |
Maps code regions to original source |
| : : files (only when optimizing existing : | |
| : : code; enables post-experiment : | |
| : : integration) : | |
initial_program.py |
Seed program with EVOLVE-BLOCK |
: : markers and ORIGIN comments : |
|
evaluator.py |
CLI-compatible evaluator script for |
: : the ae CLI : |
|
problem_description.md |
Detailed technical problem |
| : : description (used in LLM prompts) : | |
example_evaluation.json |
Sample evaluator output |
test_program.py |
Pytest tests for the initial program |
test_evaluator.py |
Pytest tests for the evaluator |
pyproject.toml |
uv project configuration |
README.md |
Experiment documentation |
*.py (multi-file only) |
Additional context files imported by |
| : : the initial program : |
What ships with it
16 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.
- examples/circle_packing/evaluator.py 5.6 KB runs code
- examples/circle_packing/example_evaluation.json 52 B
- examples/circle_packing/initial_program.py 4.3 KB runs code
- examples/circle_packing/problem_description.md 2.3 KB
- examples/circle_packing/pyproject.toml 198 B
- examples/circle_packing/README.md 1.4 KB
- examples/circle_packing/test_evaluator.py 6.7 KB runs code
- examples/circle_packing/test_program.py 2.8 KB runs code
- README.md 3.4 KB
- references/evaluator_patterns.md 18 KB
- references/evolve_block_guide.md 5.5 KB
- references/multi_file_guide.md 14 KB
- references/numerical_stability.md 7.9 KB
- references/phase_1_clarify.md 4.9 KB
- references/phase_2_implement.md 19 KB
- resources/experiment_description_schema.py 12 KB runs code
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.
- 4d ago First seen · 191 lines · 78 tokens per session scan A 70beca4f35e6
alpha-evolve-experiment-design is a skill published in the GitHub repository Google-Cloud-AI/alphaevolve-on-googlecloud (106 stars, last pushed 2d ago), licensed Apache-2.0. It adds 78 tokens to every session and 2,023 once invoked, about $0.0004 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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