flywheel-runner
Run OpenQuant notebook-to-experiment flywheel iterations (single run and grid run), capture artifacts, and summarize ranked outcomes for promotion decisions.
Skill by Open-Quant
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/open-quant-flywheel-runner
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/flywheel-runner
What's inside
- Skill name
flywheel-runner- Description
- Run OpenQuant notebook-to-experiment flywheel iterations (single run and grid run), capture artifacts, and summarize ranked outcomes for promotion decisions.
- License
- MIT
- Instructions
- 54 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Flywheel Runner Use this skill when you need to execute the research flywheel end-to-end and produce deterministic artifacts. ## What this skill does 1. Runs a baseline single experiment from TOML config. 2. Runs a grid (algo wheel) experiment from a grid TOML. 3. Produces artifact directories and leaderboard output. 4. Surfaces top run metrics and promotion flags. ## Commands ```bash # Single run uv run --python .venv/bin/python python experiments/run_pipeline.py \ --config experiments/configs/futures_oil_baseline.toml \ --out experiments/artifacts # Grid run (parameter wheel) uv run --python .venv/bin/python python experiments/run_pipeline.py \ --config experiments/configs/futures_oil_baseline.toml \ --grid-config experiments/configs/futures_oil_grid.toml \ --out experiments/artifacts ``` ## Expected outputs - Single run folder containing: - `run_manifest.json` - `metrics.parquet` - `events.parquet` - `signals.parquet` - `weights.parquet` - `backtest.parquet` - `decision.md` - Grid run folder containing: - `leaderboard.parquet` - one subfolder per run with the single-run files above ## File targets - Runner: `experiments/run_pipeline.py` - Base config: `experiments/configs/futures_oil_baseline.toml` - Grid config: `experiments/configs/futures_oil_grid.toml` - Output root: `experiments/artifacts/` ## Quality checks ```bash uv run --python .venv/bin/python pytest python/tests/test_experiment_scaffold.py -q ```
From Open-Quant/openquant, MIT.
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Verify parity between notebook-like pipeline execution and scripted experiment workflows so research findings are reproducible.
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promotion-gate
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Evaluate promotion readiness from flywheel outputs using statistical and economic gates, then produce a concise go/no-go decision note.
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feature-discovery
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Build candidate features, run feature screening and diagnostics, and prepare accepted feature sets for downstream flywheel experiments.
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artifact-auditor
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Audit experiment artifact folders for completeness, schema consistency, and promotion traceability across single and grid runs.
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Signals
- Stars
- 52
- Forks
- 6
- Open issues
- 3
- Last commit (this folder)
- Mar 4, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Open-Quant/openquant
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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- 0.506score
notebook-executor
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Execute OpenQuant notebook code cells non-interactively, persist outputs to artifact paths, and fail fast on runtime errors.
SkillDFreshness: D★ 52Claude Code +9 - 0.506score
parity-check
Open-Quant
Verify parity between notebook-like pipeline execution and scripted experiment workflows so research findings are reproducible.
SkillDFreshness: D★ 52Claude Code +9 - 0.506score
promotion-gate
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Evaluate promotion readiness from flywheel outputs using statistical and economic gates, then produce a concise go/no-go decision note.
SkillDFreshness: D★ 52Claude Code +9 - 0.506score
feature-discovery
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Build candidate features, run feature screening and diagnostics, and prepare accepted feature sets for downstream flywheel experiments.
SkillDFreshness: D★ 52Claude Code +9 - 0.506score
artifact-auditor
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Audit experiment artifact folders for completeness, schema consistency, and promotion traceability across single and grid runs.
SkillDFreshness: D★ 52Claude Code +9
Cite this page
flywheel-runner skill. Agent Mart. https://agentmart.dev/skills/open-quant-flywheel-runner (last updated 2026-10-24)