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.
npx skills add BaggaT236/AI-Trading-Skills --skill skill-idea-minergit clone --depth 1 https://github.com/BaggaT236/AI-Trading-SkillsWrote 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.
[](https://agentmods.dev/skills/baggat236/ai-trading-skills/skill-idea-miner)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/skill-idea-miner"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/skill-idea-miner/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.
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/skill-idea-miner"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/skill-idea-miner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00039 | $0.00976 |
| Opus 5 | $0.00019 | $0.00488 |
| Sonnet 5 | $0.00008 | $0.00195 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
skill-idea-miner 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 12d ago.
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.
This is a copy
100% identical to skill-idea-miner — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
pyyamlpackage - Claude CLI installed and authenticated (
claude --versionto 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
# 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
- Enumerate session logs from allowlist projects in
~/.claude/projects/ - Filter to past 7 days by file mtime, confirm with
timestampfield - Extract user messages (
type: "user",userType: "external") - Extract tool usage patterns from assistant messages
- Run deterministic signal detection:
- Skill usage frequency (
skills/*/path references) - Error patterns (non-zero exit codes,
is_errorflags, exception keywords) - Repetitive tool sequences (3+ tools repeated 3+ times)
- Automation request keywords (English and Japanese)
- Unresolved requests (5+ minute gap after user message)
- Skill usage frequency (
- Invoke Claude CLI headless for idea abstraction
- Output
raw_candidates.yaml
Stage 2: Scoring and Deduplication
- Load existing skills from
skills/*/SKILL.mdfrontmatter - Deduplicate via Jaccard similarity (threshold > 0.5) against:
- Existing skill names and descriptions
- Existing backlog ideas
- 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
- Merge scored candidates into
logs/.skill_generation_backlog.yaml
What ships with it
7 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.
- references/idea_extraction_rubric.md 6.1 KB
- scripts/__init__.py 0 B runs code
- scripts/mine_session_logs.py 28 KB runs code
- scripts/score_ideas.py 15 KB runs code
- scripts/tests/conftest.py 223 B runs code
- scripts/tests/test_mine_session_logs.py 32 KB runs code
- scripts/tests/test_score_ideas.py 8.2 KB runs code
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.
- 12d ago First seen · 109 lines · 39 tokens per session scan A 34c0ecda26c4
skill-idea-miner is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 8d ago), licensed MIT. It adds 39 tokens to every session and 976 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to skill-idea-miner, differing in 0 lines, and is treated as a copy.
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