Show Me Your Work Decision Log
cursor/plugins
Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.
Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate…
Install Factor Mining
$ npx skills add minihellboy/factorminer --skill factor-mining -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install minihellboy/factorminer factor-mining --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .claude/skills/factor-mining && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .claude/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-miningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add minihellboy/factorminer --skill factor-mining -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install minihellboy/factorminer factor-mining --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .agents/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .agents/skills/factor-mining && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .agents/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add minihellboy/factorminer --skill factor-mining -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install minihellboy/factorminer factor-mining --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .cursor/skills/factor-mining && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .cursor/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/minihellboy/factorminer.git --path integrations/factor-researcher/plugin/skills/factor-mining--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add minihellboy/factorminer --skill factor-mining -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install minihellboy/factorminer factor-mining --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .gemini/skills/factor-mining && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .gemini/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install minihellboy/factorminer factor-miningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add minihellboy/factorminer --skill factor-mining -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .github/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .github/skills/factor-mining && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .github/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add minihellboy/factorminer --skill factor-mining -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install minihellboy/factorminer factor-mining --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/minihellboy/factorminer.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/integrations/factor-researcher/plugin/skills/factor-mining .opencode/skills/factor-mining && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "factor-mining" agent skill from https://github.com/minihellboy/factorminer/tree/main/integrations/factor-researcher/plugin/skills/factor-mining into .opencode/skills/factor-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "factor-mining", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
factor-mining- GitHub stars
- 123
- Token cost
- ~781 tokens
- SKILL.md length
- 302 words
- Files
- 3 (incl. references)
- Skills in repo
- 7
- Repo updated
- First seen
- Licence
- MIT
At a glance
Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate…
- Works in 4 steps: Confirm prerequisites → Run the Ralph loop → Or run the Helix loop → …
- Generate a new factor library from a validated dataset
- SKILL.md covers Choosing the loop, Workflow, Guardrails and MCP alternative
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Factor Mining is an agent skill from minihellboy/factorminer. Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate, canonicalization). Use to generate a new factor library from a validated dataset. Triggers on "mine factors", "discover factors", "run mining", "find alpha", "helix loop", "ralph loop", "build a factor library".
Its SKILL.md is about 780 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/dsl-operators.md` and `references/loop-architecture.md`).
It sits in Agent Workflows, covering Autonomous loops. The repository describes itself as: A Self-Evolving Agent with Skills and Experience Memory for Financial Alpha Discovery. The licence is MIT.
When your agent uses it
- Generate a new factor library from a validated dataset
- Discover factors
- Build a factor library
Example prompts
- “mine factors”
- “discover factors”
- “run mining”
- “/factor-mining”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 75e0560. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Factor Mining loads about 781 tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 302 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from minihellboy/factorminer at commit 75e0560, republished under its MIT licence (© minihellboy). 302 words, ~781 tokens.
Download SKILL.mdSave it as
.claude/skills/factor-mining/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- factor-mining
- description
- Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate, canonicalization). Use to generate a new factor library from a validated dataset. Triggers on "mine factors", "discover factors", "run mining", "find alpha", "helix loop", "ralph loop", "build a factor library".
Factor Mining
This skill runs FactorMiner's self-evolving discovery loop: it retrieves memory priors, proposes candidate factor formulas with an LLM, evaluates them, and admits the survivors to a factor library.
See references/loop-architecture.md for the stage-by-stage loop design and references/dsl-operators.md for the factor-formula operator vocabulary.
Choosing the loop
| Use | When |
|---|---|
mine (Ralph loop) | Default. Paper-faithful Algorithm 1 — retrieve, generate, evaluate, admit, evolve memory. |
helix (Helix loop) | When you want Phase 2 features: do-calculus causal validation, regime-conditional evaluation, multi-specialist debate generation, or SymPy canonicalization. Drop-in superset of Ralph. |
Workflow
1. Confirm prerequisites
The dataset must already pass factor-data validation. Confirm the iteration budget — mining cost scales with iterations × batch-size.
2. Run the Ralph loop
factorminer -o output/run1 mine \
--data path/to/market_data.csv \
--iterations 40 --batch-size 16 --target 30--iterations— maximum mining iterations (the loop also stops early once--targetfactors are admitted).--batch-size— candidate factors proposed per iteration.--target— desired library size.--resume path/to/factor_library.json— continue a previous run.--mock— synthetic data + mock LLM, no API calls. Use only for smoke tests.
3. Or run the Helix loop
factorminer -o output/run1 helix \
--data path/to/market_data.csv \
--iterations 40 --batch-size 16 --target 30 \
--causal --regime --debate --canonicalizeEach --feature / --no-feature flag overrides the config; omit a flag to keep the config default. Phase 2 features cost extra compute and LLM calls — enable the ones the research question needs.
4. Inspect the result
factorminer session inspect output/run1 --jsonReport library size, iteration count, and yield rate. The factor library is written to output/run1/factor_library.json; the run log to session_log.json.
Guardrails
- Mining proposes formulas; it does not prove them. Always follow with
factor-evaluationon the held-out split. - A low yield rate usually means thresholds are too strict for the dataset, not that the data is bad — tune
ic_threshold/correlation_thresholdin config, do not silently relax them in a report. --mockoutput is never a research result; never present mock metrics as real.
MCP alternative
When the FactorMiner MCP server is connected, mine_factors and helix_mine expose the same workflow as tools, returning a structured session summary directly.
© minihellboy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (references) in integrations/factor-researcher/plugin/skills/factor-mining of minihellboy/factorminer.
- SKILL.md
- references/dsl-operators.md
- references/loop-architecture.md
Open the folder on GitHubat commit 75e0560
Compare with similar skills
Factor Mining next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Factor Mining this skillminihellboy/factorminer | 123 | — | ~781 | Automated safety check: Pass | MIT | |
| Show Me Your Work Decision Logcursor/plugins | 10k | 9 repos | ~1.6k | Automated safety check: Pass | None | |
| Autoresearch Iteration Loopuditgoenka/autoresearch | 6.5k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| PUA Looptanweai/pua | 20k | 1 repos | ~1.1k | Automated safety check: Pass | MIT | |
| AutopilotYeachan-Heo/oh-my-claudecode | 40k | 1 repos | ~4.4k | Automated safety check: Pass | MIT | |
| Install Loop Engineeringcobusgreyling/loop-engineering | 11k | 1 repos | ~648 | Automated safety check: Pass | MIT |
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More from minihellboy/factorminer
Factor Evaluation
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Evaluate a factor library — recompute Information Coefficient (IC), ICIR, win rate, and turnover on held-out data, and surface train→test decay.
Factor Backtest
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Combine a factor library into a composite signal and quintile-backtest it under transaction costs — long-short return, monotonicity, turnover, and tearsheets.
Factor Benchmark
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Run FactorMiner benchmark workflows — the Table 1 Top-K freeze benchmark, memory and strategy ablations, transaction-cost pressure tests, and the full suite.
Factor Data
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Validate, resample, and ingest market data for factor mining.
Factor Report
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Generate static reports, tearsheets, and exports from FactorMiner artifacts — markdown/HTML research notes, plots, and library exports (JSON/CSV/formulas).
Research Ingestion
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Absorb external research reports/papers into structured, retrievable hypothesis cues via FactorMiner's Report-to-Memory Absorption (RMA) service — an OHLCV-eligibility gate, a mechanism-family…
Related
Categories
Questions about Factor Mining
What does Factor Mining do?
Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate…. Factor Mining is an agent skill from minihellboy/factorminer. Discover alpha factors by running the FactorMiner research engine — the paper-faithful Ralph loop or the enhanced Helix loop (causal validation, regime conditioning, multi-specialist debate, canonicalization).
When should I use Factor Mining?
Factor Mining fits situations like: generate a new factor library from a validated dataset; discover factors; build a factor library.
How do I install Factor Mining in Claude Code?
Run `npx skills add minihellboy/factorminer --skill factor-mining -a claude-code`. Or copy the skill folder (integrations/factor-researcher/plugin/skills/factor-mining in minihellboy/factorminer) into .claude/skills/factor-mining in your project. Claude Code loads it when a task matches its description.
How do I install Factor Mining in Codex?
Run `npx skills add minihellboy/factorminer --skill factor-mining -a codex`. Or copy the skill folder (integrations/factor-researcher/plugin/skills/factor-mining in minihellboy/factorminer) into .agents/skills/factor-mining in your project. Codex loads it when a task matches its description.
Can I use Factor Mining in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add minihellboy/factorminer --skill factor-mining -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/factor-mining, .gemini/skills/factor-mining, .github/skills/factor-mining and .opencode/skills/factor-mining in your project.
What does Factor Mining need to run?
SKILL.md names no scripts, command-line tools or credentials: Factor Mining is instructions for the agent only.
Does Factor Mining access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Factor Mining safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Factor Mining use?
Factor Mining is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Factor Mining use?
About 781 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.
What are the alternatives to Factor Mining?
Skills that share tags, products or a category with Factor Mining: Show Me Your Work Decision Log (cursor/plugins, 10k stars), Autoresearch Iteration Loop (uditgoenka/autoresearch, 6.5k stars), PUA Loop (tanweai/pua, 20k stars) and Autopilot (Yeachan-Heo/oh-my-claudecode, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Factor Mining?
minihellboy (a GitHub user) maintains it in minihellboy/factorminer, which has 123 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 28, 2026.
Source: minihellboy/factorminer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.