By wrxck
Mines your Claude Code history, config, and session transcripts, spots the workflows you keep repeating, and forges them into the right artifact — a skill, subagent, hook, slash command, workflow, or a full publishable plugin. Local-only analysis; hands off to mcp-forge, behavior-hooks, and matts-second-brain where they fit.
Bundle forged artifacts into a plugin and publish to the marketplace + docs site
Scaffold an approved self-forge proposal into a real artifact
Analyze your Claude Code usage and propose a ranked list of artifacts to forge
Turns one mined signal into a concrete artifact design: which type (skill/subagent/hook/command/ workflow/plugin or a hand-off), and a precise spec. Delegate when designing a proposal before any files are written.
Writes a designed artifact's files in the exact Claude Code format and validates them. Delegate after an artifact-architect design is approved, to forge the real files.
Mines local Claude Code usage (history, transcripts, config, inventory) into a structured signal report. Delegate when a self-forge run needs the raw evidence gathered and de-noised before classification, especially over a large history.
Uses power tools
Uses Bash, Write, or Edit tools
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Turn how you actually work into reusable Claude Code artifacts.
self-forge mines your local Claude Code usage — prompt history, session transcripts, settings, and the skills/commands/agents/hooks you already have — finds the things you keep doing by hand, and forges each into the right shape: a slash command, a skill, a subagent, a hook, a workflow, or a whole publishable plugin. It proposes from the evidence of how you actually work — not from a blank page, and not from a codebase scan. All analysis stays on your machine.
Not the same as
claude-automation-recommender. That official skill reads your codebase's tech stack and recommends. self-forge reads your own behaviour — what you repeat and correct — and ranks, scaffolds, and publishes. Different axis, complementary tools.
It is the meta-tool of this marketplace: where a specialist already exists, self-forge routes to it —
CLI-wrapping to mcp-forge, corrections to
behavior-hooks, durable knowledge to
matts-second-brain, permission noise to
fewer-permission-prompts, codebase-based suggestions to claude-automation-recommender.
Every repeated prompt, every "no, always do it this way", every five-step deploy you re-explain is a latent artifact. You rarely stop to capture them. self-forge does the noticing for you: it quantifies the repetition, ranks what is worth automating, and builds it in the exact format Claude Code expects.
/plugin marketplace add wrxck/claude-plugins
/plugin install self-forge@wrxck-claude-plugins
python3 (standard library only — no pip installs).~/.claude/history.jsonl and some session history. self-forge works best after
you have used Claude Code for a while; it reads roughly your last 30 days of usage by default. On a
fresh profile it will honestly tell you there is not enough signal yet, rather than invent work.| Command | What it does |
|---|---|
/self-forge | Mine your usage, rank candidates, present a proposal report (no files written) |
/self-forge:scaffold <n> | Build one approved proposal into a real artifact |
/self-forge:publish <name> | Bundle artifacts into a plugin and publish to the marketplace + docs |
Or just ask: "what should I turn into a skill?", "analyze my Claude usage", "make a hook out of the thing I keep correcting" — the skill loads on those triggers.
/self-forge returns a ranked, evidence-anchored report — and stops there until you approve a build:
## self-forge — 3 proposals from 30d of usage
| # | Forge | Name | Evidence | Priority | Confidence |
|---|---------|----------------------------|--------------|----------|------------|
| 1 | hook | block-compose-down-volume | 7x corrected | High | 0.9 |
| 2 | command | /review-security | 12x typed | High | 0.85 |
| 3 | skill | deploy-nutrition-saas | 5x walked | Medium | 0.7 |
Scaffold any with /self-forge:scaffold <number>.
If your history is thin, it says so plainly and tells you when to come back — it never pads the list with invented suggestions. That honesty is the point: every proposal is backed by a real count.
MINE -> CLUSTER -> CLASSIFY -> SCORE -> PROPOSE -> (approve) -> SCAFFOLD -> (opt) PUBLISH
scripts/mine.py, stdlib only) reads
~/.claude/history.jsonl, samples project transcripts, and inventories what already exists. It
emits aggregate counts and short snippets of your own prompts — never assistant output, file
contents, or anything network-bound.priority = (frequency x friction x automatability) / build_cost, gated by confidence,
with a hard floor so weak ideas are dropped, not padded.skills/self-forge/ — the core skill, with references (signal-taxonomy, mining-playbook,
artifact-formats, scoring-model, publishing), templates for every artifact type, and the
miner script.agents/ — usage-miner, artifact-architect, artifact-smith for fanned-out runs.commands/ — /self-forge, /self-forge:scaffold, /self-forge:publish.All analysis is local. The miner reads files under ~/.claude and prints aggregates plus short
snippets of your own prompts to justify proposals. Nothing is uploaded.
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