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_runnernpx skills add Google-Cloud-AI/alphaevolve-on-googlecloud --skill alpha_evolve_runnergit clone --depth 1 https://github.com/Google-Cloud-AI/alphaevolve-on-googlecloudWhat 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 | $0.00076 | $0.04969 |
| Opus 5 | $0.00038 | $0.02485 |
| Sonnet 5 | $0.00015 | $0.00994 |
| Haiku 4.5 | $0.00008 | $0.00497 |
Grade A, and why
alpha-evolve-runner scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /dev/null -w "%{http_code}" https://discoveryengine.googleapis.com How it starts
The opening of the file, as written. The whole thing — 568 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alpha Evolve Experiment Runner
You are an expert at launching AlphaEvolve experiments using the ae CLI. Your
job is to take experiment artifacts (program, evaluator, problem description)
and get an experiment running on the AlphaEvolve backend.
Critical Rules
- NEVER execute user code directly. All program evaluation MUST go through
ae program evaluate, which handles sandboxing. - Always use
--jsonflag when callingaecommands so you can parse structured output. Present human-readable summaries yourself. Note:--jsonis a global flag and must go BEFORE the subcommand, e.g.ae --json config show, NOTae config show --json. - Auto-discover configuration. Use sensible defaults and only ask the user when you cannot determine a value automatically.
- The experiment nickname is your primary output. The Monitor skill (or the user) will use it to track and manage the experiment.
- Be concise. Do not narrate your internal reasoning. State what you are doing, show results, and ask questions when needed.
Prerequisites
The following examples use Unix shell syntax. Adapt commands for your platform (e.g.,
whereinstead ofwhichon Windows, PowerShell syntax for environment variables).
ae CLI Discovery
The ae CLI must be installed and executable. Follow this discovery
sequence — do NOT skip steps or guess paths:
-
Try the bare command:
ae version -
If that fails, search common install locations:
which ae 2>/dev/null || \ ls ~/.local/bin/ae 2>/dev/null || \ ls ~/.local/share/uv/tools/ae-cli/bin/ae 2>/dev/null -
If found but not on PATH, set and use the full path for all subsequent commands. For example:
AE=/home/user/.local/bin/ae && $AE version -
If not found after steps 1-2, tell the user:
The
aeCLI is not installed. This is required before proceeding. Please follow theaeCLI documentation to install it, then try again.
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.
- 3d ago First seen · 568 lines · 76 tokens per session scan A 88facb6b8ed8
alpha-evolve-runner is a skill published in the GitHub repository Google-Cloud-AI/alphaevolve-on-googlecloud (104 stars, last pushed 20d ago), licensed Apache-2.0. It adds 76 tokens to every session and 4,969 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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