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lhbsaalhbsaa/apex-unified/skills/delivery-gate/SKILL.md

delivery-gate

Skill0 starsChanged 4 months agoMITView on GitHub

Stop hook that blocks Claude from finishing until quality checks pass. Detects rationalization patterns (surface text heuristics), stale learning logs (filesystem mtime), and low disk space. Complements self-audit by mechanically enforcing learning capture habits.

3 other projects use a version of this, 2 of them edited.

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SKILL.md

Delivery Gate — Mechanical Quality Gate for Claude Code

A Stop hook that checks three things before Claude can finish a session, using only deterministic checks — file modification timestamps, disk usage, and regex patterns on the transcript text. No AI inference.

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

CheckMechanismOn Hit
Rationalization patternsRegex on transcript tailWarning only (never blocks)
Stale learning librariesmtime on 5 configurable pathsWarning if some stale; Block if >=3 stale OR growth-log stale + complex task
Disk space < 50GBshutil.disk_usageWarning
Disk space < 15GBshutil.disk_usageBlock (exit 2)

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:

VariableDefaultPurpose
RATIONALIZE4 patternsRegex patterns for rationalization detection
LIBS5 librariesFiles/dirs to check for today's updates
COMPLEX_THRESHOLD3Edit/Write calls to classify as complex
DISK_WARN_GB50Warn below this
DISK_CRIT_GB15Block below this

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

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