# skill-idea-miner

Extracts candidate skill ideas from recent Claude Code session logs, scores them, and updates a prioritized backlog.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 3100 installs · ★ 3267
- Author: tradermonty
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/skill-idea-miner/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/skill-idea-miner

## What it does

The skill inspects session logs inside `~/.claude/projects/` from the past 7 days. It scans for repetitive tool call sequences, non-zero exit codes, automation keywords, and long response gaps. Based on these signals, the `mine_session_logs.py` script runs Claude CLI in headless mode to summarize candidate ideas into `raw_candidates.yaml`.

Stage two deduplicates ideas using Jaccard similarity against existing skills and backlog entries with a 0.5 threshold. Scored candidates receive ratings for novelty (0.3), feasibility (0.3), and trading value (0.4). The resulting prioritized list lands in `logs/.skill_generation_backlog.yaml`.

You need Python 3.10+ with `pyyaml` and an authenticated Claude CLI. No dedicated API keys are needed because LLM requests route directly through the CLI.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill skill-idea-miner -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/skill-idea-miner/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/skill-idea-miner/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill skill-idea-miner -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/skill-idea-miner/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill skill-idea-miner -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/skill-idea-miner/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install tradermonty/claude-trading-skills skill-idea-miner
```

2. **Manually: put the files in place**
- File: `.github/skills/skill-idea-miner/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill skill-idea-miner -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/skill-idea-miner
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/skill-idea-miner/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill skill-idea-miner -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/skill-idea-miner/SKILL.md

## When to use it
- Extract skill ideas from recent Claude Code interaction logs
- Detect repetitive tool patterns and frequent session errors
- Filter duplicate skill ideas using Jaccard similarity scoring
- Score candidates by feasibility, novelty, and trading value

## Example prompts
- Mine new skill candidates from recent sessions: `python3 scripts/mine_session_logs.py --output-dir reports/`
- Run a dry-run log inspection without LLM scoring: `python3 scripts/mine_session_logs.py --dry-run --output-dir reports/`
- Score existing candidates and merge them into backlog: `python3 scripts/score_ideas.py --candidates reports/raw_candidates.yaml --output-dir logs/`

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 06cee3aebfae70b9.

BEGIN THIRD-PARTY FILE 06cee3aebfae70b9
````text
---
name: skill-idea-miner
description: Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions.
---

# Skill Idea Miner

Automatically extract skill idea candidates from Claude Code session logs,
score them for novelty, feasibility, and trading value, and maintain a
prioritized backlog for downstream skill generation.

## When to Use

- Weekly automated pipeline run (Saturday 06:00 via launchd)
- Manual backlog refresh: `python3 scripts/run_skill_generation_pipeline.py --mode weekly`
- Dry-run to preview candidates without LLM scoring

## Prerequisites

- **Python 3.10+** with `pyyaml` package
- **Claude CLI** installed and authenticated (`claude --version` to verify)
- **Session logs** in `~/.claude/projects/<project>/` (created automatically by Claude Code)
- No API keys required (uses Claude CLI for LLM calls)

## Workflow

### Quick Start

```bash
# Dry-run: preview mined candidates without LLM scoring
python3 scripts/mine_session_logs.py --dry-run --output-dir reports/

# Full mining with scoring (requires Claude CLI)
python3 scripts/mine_session_logs.py --output-dir reports/

# Score existing candidates
python3 scripts/score_ideas.py \
  --candidates reports/raw_candidates.yaml \
  --output-dir logs/
```

### Stage 1: Session Log Mining

1. Enumerate session logs from allowlist projects in `~/.claude/projects/`
2. Filter to past 7 days by file mtime, confirm with `timestamp` field
3. Extract user messages (`type: "user"`, `userType: "external"`)
4. Extract tool usage patterns from assistant messages
5. Run deterministic signal detection:
   - Skill usage frequency (`skills/*/` path references)
   - Error patterns (non-zero exit codes, `is_error` flags, exception keywords)
   - Repetitive tool sequences (3+ tools repeated 3+ times)
   - Automation request keywords (English and Japanese)
   - Unresolved requests (5+ minute gap after user message)
6. Invoke Claude CLI headless for idea abstraction
7. Output `raw_candidates.yaml`

### Stage 2: Scoring and Deduplication

1. Load existing skills from `skills/*/SKILL.md` frontmatter
2. Deduplicate via Jaccard similarity (threshold > 0.5) against:
   - Existing skill names and descriptions
   - Existing backlog ideas
3. Score non-duplicate candidates with Claude CLI:
   - Novelty (0-100): differentiation from existing skills
   - Feasibility (0-100): technical implementability
   - Trading Value (0-100): practical value for investors/traders
   - Composite = 0.3 * Novelty + 0.3 * Feasibility + 0.4 * Trading Value
````
END THIRD-PARTY FILE 06cee3aebfae70b9

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