delivery-gate
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. Use when Claude should be mechanica
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Static analysis is a first line of defense, not a guarantee. Read the source
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
| Check | Mechanism | On Hit |
|---|---|---|
| Rationalization patterns | Regex on transcript tail | Warning only (never blocks) |
| Stale learning libraries | mtime on 5 configurable paths | Warning if some stale; Block if >=3 stale OR growth-log stale + complex task |
| Disk space < 50GB | shutil.disk_usage | Warning |
| Disk space < 15GB | shutil.disk_usage | Block (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:
| Variable | Default | Purpose |
|---|---|---|
RATIONALIZE | 4 patterns | Regex patterns for rationalization detection |
LIBS | 5 libraries | Files/dirs to check for today's updates |
COMPLEX_THRESHOLD | 3 | Edit/Write calls to classify as complex |
DISK_WARN_GB | 50 | Warn below this |
DISK_CRIT_GB | 15 | Block 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
Files
2- SKILL.md
147a971c265.0 KB - hooks/quality-gate.py
76aa0fe8c17.6 KB
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