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Agentic Usage Guide

This guide shows how to run Shinka with coding agents using the project skills:

  • shinka-setup: scaffold task files (evaluate.py, initial.<ext>, optional run config)
  • shinka-convert: snapshot an existing repo into a Shinka task directory
  • shinka-run: launch and iterate evolution batches via shinka_run
  • shinka-inspect: load top-performing programs into a compact context bundle

It covers: - installing Shinka - installing Claude Code and/or Codex CLI - installing the skills from this GitHub repo with npx skills add - running a practical setup -> run -> inspect loop

1) Install Shinka

From a clean machine:

pip install shinka-evolve

# or
uv pip install shinka-evolve

Set API keys (example):

cp .env.example .env 2>/dev/null || true
# Edit .env and add OPENAI_API_KEY / ANTHROPIC_API_KEY as needed

2) Install Agent CLI(s)

Install one or both.

Claude Code

npm install -g @anthropic-ai/claude-code
claude --version

Codex CLI

npm install -g @openai/codex
codex --version

3) Install Skills from the Repo with npx skills add

The Shinka skills live directly in this repo under skills/. You do not need to copy files by hand or publish a separate npm package.

Install all current Shinka skills globally for Claude Code and Codex:

npx skills add SakanaAI/ShinkaEvolve --skill '*' -g -a claude-code -a codex -y

This installs from the GitHub repo source. The explicit --skill '*' makes "install all skills" unambiguous and avoids interactive prompts.

Installed skills currently include:

  • shinka-setup
  • shinka-convert
  • shinka-run
  • shinka-inspect

Project-local install

Use this if you want the skills installed only for the current repo:

npx skills add SakanaAI/ShinkaEvolve --skill '*' -a claude-code -a codex -y

Typical project paths:

  • Claude Code: .claude/skills/
  • Codex: .agents/skills/

Global install paths

For the global install command above, the relevant skill roots are:

  • Claude Code: ~/.claude/skills/
  • Codex: ~/.codex/skills/

Install one skill only

For a narrower install:

npx skills add SakanaAI/ShinkaEvolve --skill shinka-setup -g -a claude-code -a codex -y

4) Setup Skill Walkthrough (shinka-setup)

Ask the agent to scaffold a new task directory and evaluator contract.

Example prompt:

Use shinka-setup to scaffold a new task in examples/my_task.
Language: python.
Goal: maximize <metric>.

Illustration (setup flow):

Claude setup step 1

Claude setup step 2

Expected output: - initial.<ext> with evolve block - evaluate.py producing metrics.json + correct.json - optional run_evo.py / shinka.yaml scaffolds when requested

5) Run Skill Walkthrough (shinka-run)

Use shinka_run for agent-driven evolution loops.

Minimal batch:

shinka_run \
  --task-dir examples/my_task \
  --results_dir results/my_task_agent \
  --num_generations 10

With core knobs via --set:

shinka_run \
  --task-dir examples/my_task \
  --results_dir results/my_task_agent \
  --num_generations 20 \
  --set evo.max_api_costs=0.5 \
  --set evo.llm_models='["gpt-5-mini","gemini-3-flash-preview"]' \
  --set db.num_islands=2 \
  --set db.parent_selection_strategy=weighted

Illustration (run flow):

Claude run step 1

Claude run step 2

6) Inspect Skill Walkthrough (shinka-inspect)

Use shinka-inspect after one or more batches to generate an agent-ready context file.

Minimal:

python skills/shinka-inspect/scripts/inspect_best_programs.py \
  --results-dir results/my_task_agent \
  --k 5

With filters and explicit output:

python skills/shinka-inspect/scripts/inspect_best_programs.py \
  --results-dir results/my_task_agent \
  --k 8 \
  --min-generation 10 \
  --max-code-chars 5000 \
  --out results/my_task_agent/inspect/top_programs.md

Output: - default file: results/my_task_agent/shinka_inspect_context.md - contains ranking + code snippets for top programs - designed to be loaded directly into coding-agent context

7) Batch Iteration Rules (Important)

When using shinka-run skill:

  • unless user explicitly requests fully autonomous execution, ask for config confirmation between batches
  • keep --results_dir the same across continuation batches so prior state can reload
  • change --results_dir only when intentionally forking a new run

8) Quick Validation Checklist

Before first run:

  • shinka_run --help works
  • task dir has evaluate.py + initial.<ext>
  • API keys are available in environment
  • npx skills list shows the installed Shinka skills
  • for global installs, skills appear under ~/.claude/skills/ and/or ~/.codex/skills/
  • for project installs, skills appear under .claude/skills/ and/or .agents/skills/

After each batch:

  • check run artifacts/logs under the chosen results_dir
  • review score and correctness trend
  • run shinka-inspect and review the generated context markdown
  • choose next batch config (budget, models, islands, attempts, generations)