What is shinka-setup?

A setup tool for ShinkaEvolve, a framework that improves programs through repeated evaluation and code changes. It creates an evaluation script and a starting program for an optimization task.

Use it to create new optimization tasks, evaluation harnesses, or baseline programs in Python or another supported language.

It gives ShinkaEvolve the files it needs to measure results and know which program to improve.

shinka-setup — Skill for Claude Code and Codex by SakanaAI

About the project

ShinkaEvolve is a framework that combines large language models with evolutionary algorithms to improve scientific programs through repeated code variation and evaluation. Researchers and developers use it to explore and optimize code for scientific discovery. Its catalogue skills guide coding agents through setup, conversion, evolution, and result inspection.

SakanaAI/ShinkaEvolve · 1,376 stars · on GitHub · sakanaai.github.io

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 SakanaAI/ShinkaEvolve --skill shinka-setup

Clone the repo

git clone --depth 1 https://github.com/SakanaAI/ShinkaEvolve

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/sakanaai/shinkaevolve/shinka-setup/github.svg)](https://agentmods.dev/skills/sakanaai/shinkaevolve/shinka-setup)

Your own site

<a href="https://agentmods.dev/skills/sakanaai/shinkaevolve/shinka-setup"><img src="https://agentmods.dev/badge/skills/sakanaai/shinkaevolve/shinka-setup/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/sakanaai/shinkaevolve/shinka-setup"><img src="https://agentmods.dev/badge/skills/sakanaai/shinkaevolve/shinka-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,144 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 warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 25
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

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	$0.00062	$0.02144
Opus 5	$0.00031	$0.01072
Sonnet 5	$0.00012	$0.00429
Haiku 4.5	$0.00006	$0.00214

Measured 10d ago against content hash 6f8176e18eb7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

shinka-setup 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/run_evo.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.

skills/shinka-setup/SKILL.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Shinka Task Setup Skill

Create a setup scaffold consisting of an evaluation script and initial solution for an optimization problem given a user's task description. Both ingredients will be used within ShinkaEvolve, a framework combining LLMs with evolutionary algorithms to drive code optimization.

When to Use

Invoke this skill when the user:

Wants to optimize code with LLM-driven code evolution (Shinka/ShinkaEvolve)
No evaluate.py and initial.<ext> exist in the working directory

User Inputs

Task description + success criteria
Target language for initial.<ext> (if omitted, default to Python)
What parts of the script to optimize
Evaluation metric(s) and score direction
Number of eval runs / seeds
Required assets or data files
Dependencies or constraints (runtime, memory)

Workflow

Check if all user inputs are provided and ask the user follow-up questions if not inferrable.
Inspect working directory. Detect chosen language + extension. Avoid overwriting existing evaluate.py or initial.<ext> without consent.
Write initial.<ext> with a clear evolve region (EVOLVE-BLOCK markers or language-equivalent comments) and stable I/O contract.
Write evaluate.py:
- Python initial.py: call run_shinka_eval with experiment_fn_name, get_experiment_kwargs, aggregate_metrics_fn, num_runs, and optional validate_fn.
- Non-Python initial.<ext>: run candidate program directly (usually via subprocess) and write metrics.json + correct.json.
Ensure candidate output schema matches evaluator expectations (tuple/dict for Python module eval, or file/CLI contract for non-Python).
Validate draft evaluate.py before handoff:
- Run a smoke test:
  - python evaluate.py --program_path initial.<ext> --results_dir /tmp/shinka_eval_smoke
- Confirm evaluator runs without exceptions.
- Confirm a metrics dict is produced (either from aggregate_fn or metrics.json) with at least:
  - combined_score (numeric),
  - public (dict),
  - private (dict),
  - extra_data (dict),
  - text_feedback (string, can be empty).
- Confirm correct.json exists with correct (bool) and error (string) fields.
Ask the user if they want to run the evolution themself or whether to use the shinka-run skill:
- If the user wants to run evolution manually, add run_evo.py plus a shinka.yaml config with matching language + init_program_path.
- Ask the user if they want to use the shinka-run skill to perform optimization with the agent.

Read the full file on GitHub · 233 lines

Files

What ships with it

2 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.

10d ago First seen · 233 lines · 62 tokens per session scan A 6f8176e18eb7

Subscribe to this mod's changes

shinka-setup is a skill published in the GitHub repository SakanaAI/ShinkaEvolve (1,376 stars, last pushed 19d ago), licensed Apache-2.0. It adds 62 tokens to every session and 2,144 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.

Testing

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

tika-eval-compare

Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".

apache/tika · 50 tokens

neuron-evaluation-engineer

Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…

neuron-core/neuron-ai · 77 tokens

shinka-setup