ImpactGate: A merge gate that scores the structural decay AI adds

原始链接: https://github.com/officefloor/ImpactGate

Hacker News 的讨论聚焦于 **ImpactGate**,这是一个旨在评估人工智能生成的代码如何导致项目“结构性腐烂”的新 GitHub Action。 社区反应不一。支持者认为监测圈复杂度(cyclomatic complexity)等指标很有价值,尤其是在 AI 密集型工作流中,分支逻辑容易变得过于嵌套。其他人则建议,与其作为一个独立项目,不如将其整合到现有的代码分析工具中。 讨论中很大一部分内容在批评该项目的展示方式,多位用户对该工具及其营销中表现出的“随意编码”(vibe-coded)性质表示怀疑。批评者认为,代码库和文档中大量使用 AI,使得人们难以衡量开发者真正的专业知识和对项目的掌控力。尽管存在怀疑,但一些参与者承认,其背后的核心理念——衡量代码变更的“爆炸半径”或影响——对于 AI 和人类编写的代码来说,依然是一种实用的做法。
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原文

Measure and gate the structural decay a change introduces. Run it as a standalone CLI, a git pre-commit hook, or a plugin in GitHub, GitLab, and Jenkins CI.

Website: https://impactgate.officefloor.net

Structural decay is complexity accreting into existing structures. A god-method grows another branch. A god-class gains another method. The gate scores a change against a base (main by default) with the change-impact measure:

impact = files_changed * Σ max(WMC_other, 1) * CC * Δlines      (over changed functions)

WMC_other is the complexity already in the container you are editing. It is measured on the pre-change state. So importing a brand-new file or class is cheap. Nothing was there before. Piling onto an already-heavy class is expensive. That is the decay signal.

For the reasoning behind the formula, see Measuring the Blast Radius of Change on the OfficeFloor blog.

When impact is too high, the gate asks you to simplify the change or refactor the code it touches. It can warn (report only) or block (fail the build).

pip install impact-gate         # installs the `impact-gate` command

Or run it without installing anything, via the published image (git is bundled; mount the repo to score at /repo):

docker run --rm -v "$PWD:/repo" ghcr.io/officefloor/impact-gate \
  score --mode range --base origin/main

To hack on it locally, install from a checkout instead:

python -m venv .venv && . .venv/bin/activate
pip install -e '.[dev]'         # editable install plus the test deps
# The commit you are about to make (pre-commit): staged vs HEAD. This is the default.
impact-gate score

# Uncommitted local edits: working tree vs HEAD.
impact-gate score --mode worktree

# CI or PR review: the committed branch vs main (merge-base..HEAD).
impact-gate score --mode range --base origin/main --format json

# Set thresholds and enforcement. You can also put these in .impact-gate.yml.
impact-gate score --warn-at 50000 --block-at 200000 --enforcement block

Exit codes. 0 means ok or warn (the change is allowed). 2 means blocked (impact too high under --enforcement block). 1 means a usage or environment error.

Every report also lists the files to consider for refactoring, ranked by their share of the impact. The change-level number gates; the per-file ranking points at where the decay is concentrating, so a file quietly growing into a god-class surfaces as a candidate before it blocks anything.

A source file whose diff is larger than max_diff_lines (200,000 by default, in the measure config) is almost always a generated dump or a vendored blob. The gate skips it so it neither distorts the number nor slows scoring, and lists it under skipped so the result is never silently wrong.

Use as a git pre-commit hook

Gate every commit locally, before CI:

# Installs .git/hooks/pre-commit. It scores the staged change on each commit.
impact-gate install-hook

With enforcement: block in .impact-gate.yml, a commit whose impact is too high is blocked; on warn (or off) the report prints and the commit proceeds. Re-run with --force to overwrite an existing pre-commit hook.

Prefer the pre-commit framework? This repo ships a hook definition — add to your .pre-commit-config.yaml:

repos:
  - repo: https://github.com/officefloor/ImpactGate
    rev: v0.3.0
    hooks:
      - id: impact-gate

Grade against a distribution (the curve)

A raw threshold is hard to set: a typical change's impact varies by orders of magnitude across languages and projects. Instead of guessing a number, grade a change by its percentile against a distribution, and gate on the percentile.

# Build (or refresh) the project's own impact distribution from the merged history.
# Writes .impact-gate-baseline.json. Re-run it as the branch moves.
impact-gate baseline --base-ref main

# Gate on the grade instead of an absolute number.
impact-gate score --curve --warn-percentile 90 --block-percentile 98

The grade blends two distributions:

  • a seed prior shipped with the tool — per-language percentile tables built from a 20-repo open-source corpus, with a pooled fallback for languages not in the table;
  • the project baseline — the repo's own per-change distribution, walked from the merged mainline (only landed work; in-flight branches are never reached).

The blend weights the project by w = n / (n + K), where n is the number of landed changes behind the baseline and K (curve_prior_weight, default 200) is how much history it takes to trust the project over the seed. A fresh repo with no baseline file grades on the seed alone; a deep history leans on itself. The grade shows in every format next to the raw number.

Configure with .impact-gate.yml (repo root)

warn_at: 50000          # impact above which to warn
block_at: 200000        # impact above which to block
enforcement: warn       # off, warn, or block. Start on warn. Flip to block when ready.
tolerance: 1.0          # CI-adjustable multiplier on both thresholds. Above 1 is more lenient.
# measure_config: .impact-measure.yml   # optional: ignore globs and language overrides

# Grading curve (percentile gate). When enabled, warn_at/block_at are ignored and the
# gate uses the percentiles below instead.
curve_enabled: false           # gate on the percentile grade instead of absolute numbers
warn_percentile: 90            # grade at or above this warns
block_percentile: 98           # grade at or above this blocks
curve_prior_weight: 200        # K in w = n/(n+K): history needed to trust the project over the seed
baseline_file: .impact-gate-baseline.json   # where `impact-gate baseline` caches the distribution

CLI flags override the file. A CI job can pass --tolerance or --warn-at. So a team can dial tolerance without editing the repo. The curve knobs have flags too: --curve, --warn-percentile, --block-percentile, --baseline-file.

Add a workflow to your repo. The action scores the PR branch against its base and writes a summary. fetch-depth: 0 is required so the base branch and merge-base are present.

name: Change impact
on: pull_request
permissions:
  contents: read
  pull-requests: write         # so the action can post the score as a PR comment
jobs:
  impact:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v5
        with:
          fetch-depth: 0
      - uses: officefloor/ImpactGate@v0
        with:
          enforcement: warn        # switch to block when ready
          # warn-at: 50000
          # block-at: 200000
          # tolerance: 1.0

The score appears in the job summary and as a sticky comment on the PR (one comment, updated each run). In block mode the job fails when impact exceeds the block threshold. Make the check required in branch protection to gate merges. The comment needs pull-requests: write. Without it the run still passes and just skips the comment.

A ready-made job is in ci/gitlab-ci.yml. Copy it into your .gitlab-ci.yml, or include it remotely:

include:
  - remote: 'https://raw.githubusercontent.com/officefloor/ImpactGate/v0/ci/gitlab-ci.yml'

It runs on merge-request pipelines, scores the MR against its base ($CI_MERGE_REQUEST_DIFF_BASE_SHA) with the published Docker image, and — when a CI/CD variable GITLAB_TOKEN with the api scope is set — posts a sticky note to the MR (one note, updated each run). Without the token it still scores and gates; it just skips the note. In block enforcement the job fails when impact is too high; make it required in the merge request settings to gate merges.

A pipeline snippet is in ci/Jenkinsfile. It runs the Docker image on an agent with Docker, scoring the change against its target branch (origin/${CHANGE_TARGET:-main}) and archiving the report. In block enforcement the stage fails when impact is too high. Posting the score back to the PR/MR is left to your SCM integration; to post it with the tool itself, run impact-gate comment in the container with the provider's token and env set.

  • Core CLI. Score staged, worktree, or range. Warn or block. Text, JSON, markdown. Done.
  • GitHub Action. Composite action, job-summary report, and a sticky PR comment. Done.
  • Baseline and grading curve. impact-gate baseline profiles the project history; the gate blends a seed-corpus prior with the project's own distribution and grades a change by its percentile (score --curve). Done.
  • Distribution. pip install impact-gate, a ghcr.io/officefloor/impact-gate Docker image for any CI, and a version-tagged Action (@v0). Done.
  • More CI plugins. A GitLab CI template and a Jenkins pipeline snippet, both wrapping the Docker image (ci/gitlab-ci.yml, ci/Jenkinsfile). GitLab posts a sticky MR note. Done.
  • Hooks. impact-gate install-hook installs a git pre-commit hook, and a .pre-commit-hooks.yaml supports the pre-commit framework. Done.
  • IDE. Editor integration over LSP, with a live gauge as you edit.
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