Plumbline

Write-time intelligence for AI-generated code.

Plumbline is an MCP server that makes AI coding agents work against your project's reality — not their priors. It injects project knowledge before the agent writes, runs mutation testing before you commit, and keeps multi-step work from going off the rails.

One install. One server. Eight tools. One spotter hook.

pip install plumbline-ai[all]

What it does

Quick start

Add to your .mcp.json:

{
  "mcpServers": {
    "plumbline": {
      "command": "plumbline-mcp"
    }
  }
}

Or run plumbline setup for guided configuration including the /btw hook.

Tools

Context (know your project)

• plumbline_context — Project intelligence at session start. Conventions, pitfalls, decisions, hot files.
• plumbline_query — Search project knowledge mid-task.
• plumbline_co_changes — Files that change together. Read them before you edit.

Verify (catch mistakes)

• plumbline_verify — Pre-commit mutation testing on staged changes. Reports surviving mutants as questions: "Your code still passes tests if X is changed to Y. Is that intentional?"
• plumbline_explain — Understand a finding in detail.

Gate (stay disciplined)

• plumbline_init — Start tracking a development plan.
• plumbline_advance — Move through phase gates with evidence. The gate validates your evidence is real, not bare assertions.
• plumbline_status — Check where you are.

The /btw hook

Plumbline includes a spotter hook that fires before every file write. It doesn't wait for the agent to ask for help — it injects relevant context when the agent is about to edit a file.

/btw — src/auth.py usually changes with:
  - tests/test_auth.py
  - middleware/session.py
Did you read these before editing?

The agent never asked. The spotter saw what was happening and briefed it.

v0.1.0 ships at INFORM level — the hook injects context but does not block writes. GATE level — pre-write blocking via mutation analysis of the proposed content — ships in v0.2.0.

Health check

plumbline doctor

Shows which engines are installed and healthy.

Architecture

Plumbline wraps three proven engines under one surface:

• Context — powered by Sentinel (project intelligence from git history)
• Verify — powered by Seraph (mutation testing, static analysis)
• Gate — powered by Morpheus (plan state, phase gates, evidence validation)

Each engine is optional — install what you need:

pip install plumbline-ai[context]    # just project intelligence
pip install plumbline-ai[verify]     # just code verification
pip install plumbline-ai[gate]       # just plan enforcement
pip install plumbline-ai[all]        # everything

Why

AI coding agents skip optional quality checks every time. Not sometimes — every time. We measured this across 49 tool invocations, 9 controlled experiments, and 5 production projects.

Advisory feedback (letter grades, suggestions, warnings) has a 0% action rate. Blocking gates have a ~100% action rate.

Plumbline doesn't advise. It enforces — through evidence-gated task advancement, mutation-based commit verification, and write-time context injection.

Roadmap

v0.1.0 (current): 8 MCP tools + /btw INFORM hook. Pre-commit verification. Plan-state gating. Project intelligence injection.

v0.2.0: plumbline_check returns — pre-write blocking via the /btw hook automatically running mutation analysis on proposed file content before the Write/Edit tool call completes.

v0.3.0: Debrief loop — post-session /plumbline:debrief skill that interviews the agent and feeds hook tuning back into the signal-to-noise optimizer.

License

MIT.

Built by Evolving Intelligence AI.