# I built a Claude Code skill that discovers which automations to build — by mining my own work > Source: > Published: 2026-06-18 05:34:53+00:00 Most automation projects build *an* automation. This one builds a system that **discovers which automations to build** — by mining your own recent work — and then packages the high-confidence ones into reusable tools. It's a self-improving skill for [Claude Code](https://claude.com/claude-code). You feel it but rarely measure it: the same multi-step sequence done by hand for the third time. A focused bug-fix → branch → conventional commit → PR cycle. A QA-sweep dispatch. A release deploy. Each repetition is a signal that an abstraction is missing — but nobody systematically *finds* those signals. They're scattered across git history, terminal sessions, and memory. `distill-workflows` does `distill-workflows` is a Claude Code skill that turns that scattered signal into reusable tooling, in one pass: `*.jsonl` ) — repeated bash command patterns The diagram above maps the flow left-to-right: **Signal Sources → Scanner ( scan.sh) → Distill Engine → Packaging → Outputs**, with a A few design choices worth calling out: Run against its own repo, the scanner surfaced a pattern repeated **50+ times** that nobody had abstracted: a single-concern Android/Kotlin fix shipped as a small PR with the same conventions every time (branch naming, conventional commit scope, base branch, size limit, no AI attribution). The engine packaged it into an `android-fix-pr` skill — exactly the kind of convention layer the generic `commit` /`create-pr` tools don't encode. The higher-frequency QA-sweep pattern was *also* detected, but the engine correctly declined to package it: it already existed as a parameterized workflow. Knowing when **not** to build is half the value. `SKILL.md` procedure the agent follows.`scan.sh` signal miner — `jq` over transcripts, `git log` shape analysis, `gps recall` , artifact inventory — emitting one structured report.`watchlist.md` ledger for cross-session frequency.*Built with Claude Code. The core idea generalizes well beyond one repo: point a discovery loop at your own work history, score what repeats, and let the high-confidence patterns become tools.*