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RepoRipple

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Deterministic repository change-impact analysis for engineers and coding agents.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON â–¾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for RepoRipple, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
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Documentation Overview

RepoRipple

Know what a code change can break before you merge it.

PyPI Python versions CI License: MIT MCP Registry

RepoRipple is a local-first change-impact analyzer for engineers and coding agents. It builds a lightweight dependency graph from a repository, reads the current Git diff, traces reverse dependencies, recommends relevant tests, and emits a review-ready Markdown or JSON report.

The deterministic analyzer requires no API key, hosted service, source upload, or framework integration. An optional, explicitly requested OpenRouter explanation can turn its anonymized evidence into a short narrative without changing the underlying analysis.

PyPI · Portfolio case study · MCP setup · v0.2.0 release

RepoRipple traces a Git change through its dependency blast radius and produces a focused risk report

Why RepoRipple?

Code graphs explain how a repository is connected. RepoRipple applies that graph to the change in front of you:

  • Which files depend on the code I changed?
  • How far does the blast radius travel?
  • Which tests are most relevant?
  • Did I touch authentication, payments, deployment, or another sensitive area?
  • Should this pull request be blocked for additional review?
  • What structured context should I give a coding agent?

Install and run

Terminal
pip install reporipple

# Analyze staged, unstaged, and untracked changes.
reporipple .

# Compare a feature branch with main.
reporipple . --base origin/main

# Generate machine-readable context for an agent or automation.
reporipple . --base origin/main --format json --output impact.json

# Fail CI when a change reaches high risk.
reporipple . --base origin/main --fail-on high

# Audit the exact anonymized OpenRouter request without sending it.
reporipple . --base origin/main --explain-preview

Run it once without installing:

bash
uvx reporipple . --base origin/main

Three product surfaces

SurfaceBest forOutput
CLILocal review, scripts, and CI gatesMarkdown or JSON impact report
GitHub ActionPull-request evidence and risk thresholdsJob summary, artifact, and optional stable PR comment
MCP serverCodex, OpenCode, Cursor, Claude Code, and VS CodeTyped forecast_change and analyze_worktree tools

GitHub Action

Add RepoRipple to a pull-request workflow to create Markdown and JSON impact reports and append the Markdown report to the GitHub job summary:

yaml
name: RepoRipple

on:
  pull_request:

permissions:
  contents: read

jobs:
  impact:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@d23441a48e516b6c34aea4fa41551a30e30af803 # v6
        with:
          fetch-depth: 0
          persist-credentials: false
      - id: reporipple
        uses: adiarora06/RepoRipple@8e571fa042212fbed09db042c9c736359bd380f2 # v0.2.0
        with:
          base: ${{ github.event.pull_request.base.sha }}
      - uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5
        with:
          name: reporipple-impact
          path: |
            ${{ steps.reporipple.outputs.markdown-report }}
            ${{ steps.reporipple.outputs.json-report }}

The Action accepts path, base, max-depth, fail-on, and reports-directory. It outputs markdown-report, json-report, and risk-level. For reproducible builds, pin RepoRipple to a release commit SHA and use fetch-depth: 0 so the requested base revision is available.

This repository's own pull-request workflow demonstrates a fork-safe commenting design. Analysis runs with read-only contents access. A separate job updates one stable RepoRipple comment only for branches in the same repository; fork pull requests keep their report in the job summary and downloadable artifact without receiving a write-capable token.

Coding-agent tools (MCP)

RepoRipple can expose the same deterministic analysis to Codex, OpenCode, Cursor, Claude Code, and VS Code over a local, read-only MCP server. From a source checkout:

bash
uv run reporipple mcp --root /path/to/allowed/workspace

Launch the published package without a clone:

bash
uvx reporipple mcp --root /path/to/allowed/workspace

The server provides forecast_change for proposed edits and analyze_worktree for actual Git changes. See the MCP setup guide for client-specific commands and configuration.

The architecture guide explains how the CLI, GitHub Action, MCP server, and optional explanation layer share one deterministic analysis engine.

Example report

markdown
# RepoRipple impact report: checkout-service

**Risk:** `high` · **Graph:** 84 files / 137 dependency edges

## Changed files
- `src/billing/store.py`

## Impacted files
- `src/billing/service.py` — distance 1 via `store.py` → `service.py`
- `src/api/checkout.py` — distance 2 via `store.py` → `service.py` → `checkout.py`

## Suggested verification
- `tests/test_billing_service.py`
- `tests/test_checkout.py`

How it works

  1. Discovers Python, JavaScript, and TypeScript source files.
  2. Extracts Python imports with the standard-library AST and relative JS/TS imports with a focused parser.
  3. Builds forward and reverse dependency relationships.
  4. Gets changed files from an explicit base revision or the local worktree.
  5. Traverses dependents to a configurable depth.
  6. Adds test recommendations, documentation reminders, and deterministic risk signals.

The core intentionally avoids LLM scoring. Results stay reproducible, private, fast, and usable in CI. Optional AI explanations can be layered over the JSON output without making correctness depend on a model.

Optional OpenRouter explanation

AI explanation is off by default and is activated only by --explain. The deterministic risk level, evidence, report, and --fail-on exit status remain authoritative even if OpenRouter is unavailable or returns an invalid response.

First inspect the exact key-free body that would leave your machine:

bash
reporipple /path/to/repository --base main --explain-preview

The preview does not read an API key and does not make a network request. When you are satisfied with the payload, provide the key through the environment and explicitly request an explanation:

server.ts
export OPENROUTER_API_KEY="your-key"
reporipple /path/to/repository --base main --explain

There is no command-line key option and RepoRipple does not read a key from a file. The integration uses only the Python standard library and applies all of these controls to every request:

  • Repository names, paths, source, diffs, scanner-warning text, and user identifiers are not transmitted.
  • Files and risk signals become opaque evidence IDs such as E001; returned IDs are schema-validated and mapped back to labels locally.
  • The response must satisfy a strict JSON Schema, and unknown evidence IDs or extra fields are rejected.
  • OpenRouter routing requires zero data retention (zdr: true), denies data collection, and selects only providers that support every requested parameter.
  • Provider prices are capped at $0.25 per million input tokens and $1 per million output tokens, with a 450-token response limit.
  • Requests have a 10-second timeout and retry at most once after an explicit retryable HTTP response; ambiguous network timeouts are not retried.
  • Token usage and reported request cost are included in Markdown and JSON output.

The pinned default model is openai/gpt-6-luna. Override it with --explain-model or REPORIPPLE_OPENROUTER_MODEL; privacy, schema, and price controls remain mandatory. Privacy filters may reduce provider availability, and the request fails closed when no eligible provider satisfies them. OpenRouter's ZDR policy prevents eligible providers from retaining prompts and responses after processing; it does not mean the request stays on your machine. See OpenRouter's structured outputs, ZDR controls, and provider routing controls.

CLI reference

text
reporipple [PATH]
  --base REVISION       compare REVISION...HEAD
  --changed PATH        analyze an explicit path; repeat as needed
  --max-depth N         reverse dependency traversal depth (default: 4)
  --format markdown|json
  --output FILE
  --fail-on medium|high
  --explain             request an optional privacy-filtered OpenRouter explanation
  --explain-preview     show the exact sanitized request without sending it
  --explain-model NAME  use a pinned provider/model slug for either explanation mode

reporipple mcp
  --root PATH            restrict tool access to PATH and its descendants

When no base or explicit path is supplied, RepoRipple analyzes staged, unstaged, and untracked files. On a clean checkout it falls back to the latest commit.

--explain and --explain-preview are mutually exclusive. With JSON output, either flag returns a wrapper containing deterministic_report plus the explanation or preview; ordinary JSON output is unchanged.

Supported analysis

Read the full README →View source on GitHub →

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Reviews

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Frequently Asked Questions about RepoRipple

We don't have a confirmed install command for RepoRipple yet, so we don't publish a generated one — a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/adiarora06/RepoRipple) for the current steps.

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Technical Specs & Signals

Category💻Developer Tools
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Last updatedSep 28, 2026
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27Quality signal: Emerging · 27/100How this signal is calculated ▾
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Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

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