Plumbline — AI skill for Claude Code
Repo-level AI coding readiness assessment, in Go.
How to install Plumbline
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open sroberts/plumbline and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Plumbline does
Repo-level AI coding readiness assessment, in Go. Maps a repository to its level on the AI Codebase Maturity Model (ACMM).
Alternatives in AI
- Codebase Digest — 🗜️ Codebase-digest is your AI-friendly codebase packer and analyzer 375 ★
- Agentpet — A desktop pet for macOS & Windows that monitors your AI coding agents (Claude Code, Codex, Cursor, Gemini 334 ★
- Crux — Taking the pi coding agent to Claude Code-level performance: 0.539 → 0.773 pass@1 on Terminal-Bench 2.1 with t 187 ★
README
plumbline

Repo-level AI coding readiness assessment, in Go.
Plumbline scans a repository, looks for the feedback loops that make AI-driven development reliable (instruction files, coverage gates, nightly suites, automated triage, issue-to-PR pipelines), and reports which level of the **AI Codebase Maturity Model (ACMM)** the repo sits at. Detection is deterministic — no LLM calls, no network.
Based on Andy Anderson's paper [*The AI Codebase Maturity Model: From Assisted Coding to Self-Sustaining Systems*](https://arxiv.org/abs/2604.09388v1) (the paper's `.md` is included as `the_ai_codebase_maturity_model.md`, converted from PDF via Microsoft MarkItDown). See **[Deviations from the source paper](#deviations-from-the-source-paper)** below for where this implementation deliberately diverges.
Install
go install github.com/sroberts/plumbline/cmd/plumbline@latest
Pre-built binaries (darwin / linux × amd64 / arm64) ship on the [Releases](https://github.com/sroberts/plumbline/releases) page once a version is tagged.
Quick start
# Bare invocation: opens the Bubble Tea TUI on a terminal.
plumbline
# Pipe / CI: full report as TOON (compact, diff-friendly).
plumbline | tee maturity.toon
# Machine-readable verdict for an LLM tool harness.
plumbline --json
# Stream progress events to stderr while the scan runs.
plumbline --json --events ndjson 2>events.log >verdict.json
# CI gate: fail if not at level 3.
plumbline --fail-below 3 --quiet
# Write a committable maturity-state artifact (.plumbline.toon by default).
plumbline snapshot
plumbline snapshot --format yaml # or json
# Drill into one signal's status, evidence, and fix recipe.
plumbline inspect l2.agent-instructions
# Scaffold a missing artifact (dry-run; --apply to actually write).
plumbline fix l2.agent-instructions
plumbline fix l2.agent-instructions --apply
# Install a Claude Code skill so AI agents in your repo know how to drive plum
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