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delivery-gate

Check learning-log timestamps, free disk space, and shortcut-related phrases before Claude Code ends a session. A Stop hook, which runs when the agent tries to finish, warns or blocks completion according to configured rules without using AI judgment.

OriginalShow the original description

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 mechanically blocked from declaring work finished before quality checks and learning capture actually pass.

AI rating90/ 100See how to install

Good for

  • Checking learning records after complex editing tasks
  • Blocking completion when disk space is critically low
  • Flagging phrases that suggest skipped checks
  • Combining mechanical checks with self-audit

Overview

What it does

Checks learning-record timestamps, free disk space, and specific phrases near the end of the conversation when Claude Code tries to finish. Registered as a Stop hook, it issues warnings or blocks completion according to configured conditions. Decisions use file timestamps and regular expressions, without AI inference.

When it helps

Use it to maintain the habit of recording lessons and decisions after editing several files. It also checks for insufficient disk space and signs of skipped steps, such as postponing tests. It can work alongside self-audit, which reviews content quality.

Example requests

  • “Set up a hook that checks learning records and free disk space when work finishes.”
  • “Change the learning-record paths to match this project’s structure.”

Notes

Requires Python 3.8 or later and supports Windows, macOS, and Linux, using only the standard library. You must place quality-gate.py and register it in ~/.claude/settings.json. It checks whether records were updated, not whether their contents are correct. Phrase detection only warns because false positives are possible. It does not run builds or tests.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt explicitly checks timestamps, disk space, and conversation phrases at completion, issuing warnings or blocking termination.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
BPartly lackingConfiguration examples and exit codes are specific, but explanations conflict about updated-record counts and blocking conditions.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodIt defines local checks and completion blocking, limiting phrase-based false positives to warnings.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodIt specifies Python 3.8+, supported operating systems, script installation commands, and hook registration configuration.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (2)

  • SKILL.md5.1 KB
  • hooks/quality-gate.py7.6 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

From the ECC repository root:

mkdir -p ~/.claude/scripts
cp skills/delivery-gate/hooks/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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