Delivery Gate

This is distinct from reasoning gates (like self-audit): delivery-gate checks machine-verifiable facts; self-audit checks output quality across four reasoning dimensions. Together they form defense in depth:

• delivery-gate: "Was the learning library touched today? Is disk space safe?"
• self-audit: "Is the file content correct, complete, and honest?"

This is the same pattern as CI pipeline gates — automated, deterministic checks that verify machine-readable facts rather than trusting self-reported status.

What It Checks

Rationalization detection warns about patterns like "skip tests for now" and "pre-existing bug" — surface signals that thinking may have been cut short. It never blocks on its own, because regex heuristics can false-positive. The blocking conditions are: disk critical, >=3 learning libs stale, OR growth-log specifically stale (all require complex task >=3 edits).

Why

Claude Code's built-in checks cover code quality (build → type → lint → test). But there's a different failure mode: the agent produces working code while the session hygiene was neglected — learning not captured, rationalized shortcuts, disk running out silently.

Over many sessions of "ship and forget," the human hasn't grown. This hook enforces the habit: complex task → must touch learning libraries.

Install

cp quality-gate.py ~/.claude/scripts/

Add to ~/.claude/settings.json:

{
  "hooks": {
    "Stop": [{
      "hooks": [{
        "type": "command",
        "command": "python3 ~/.claude/scripts/quality-gate.py",
        "timeout": 5000
      }]
    }]
  }
}

Learning Libraries

Create these files in your project's memory directory. The hook checks if at least one was updated today:

memory/
├── growth-log/          # Daily learning entries (directory)
├── decisions/log.md     # Decision log
├── output-index.md      # Index of session outputs
├── ratings-tracker.md   # Skill ratings over time
└── tooling_capabilities.md  # Known tools inventory

Customize the LIBS dict to match your own file structure.

Configuration

Edit quality-gate.py:

Examples

Simple session — allowed:

edit_count=1 (< 3, not complex) → exit 0

Complex task, learning captured — allowed:

edit_count=5 (complex) → checks LIBS → growth-log updated today → exit 0

Complex task, no learning — BLOCKED:

edit_count=4 (complex) → checks LIBS → all 5 stale → exit 2
stderr: "Blocked: complex task completed but no learning captured today."

Low disk space — BLOCKED:

disk_free=12GB < 15GB critical → exit 2
stderr: "Blocked: disk space at 12GB (threshold: 15GB)."

Limitations

The hook enforces the habit of touching learning libraries, not the quality of what was recorded. If output-index.md is updated but growth-log is skipped, the hook passes (1 of 5 libraries touched). This is by design: mechanical gates check machine-verifiable facts. For content quality verification, pair with self-audit.

Compatibility

• Python 3.8+ (uses from __future__ import annotations)
• Cross-platform: Windows, macOS, Linux
• Zero dependencies beyond stdlib

Quality

This code went through 4 rounds of automated code review (CodeRabbit + Greptile) with 9 real bugs found and fixed.

See Also

• self-audit — Reasoning quality gate (completeness/consistency/groundedness/honesty)
• verification-loop — Code quality checks (build/type/lint/test)
• gateguard — PreToolUse safety gate