惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

人人都是产品经理
人人都是产品经理
W
WeLiveSecurity
Recorded Future
Recorded Future
P
Privacy & Cybersecurity Law Blog
V
Vulnerabilities – Threatpost
C
Cybersecurity and Infrastructure Security Agency CISA
G
GRAHAM CLULEY
S
Securelist
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
小众软件
小众软件
The Hacker News
The Hacker News
The Cloudflare Blog
D
Darknet – Hacking Tools, Hacker News & Cyber Security
V
V2EX
C
Cisco Blogs
Cisco Talos Blog
Cisco Talos Blog
腾讯CDC
Recent Announcements
Recent Announcements
Jina AI
Jina AI
K
Kaspersky official blog
The GitHub Blog
The GitHub Blog
云风的 BLOG
云风的 BLOG
酷 壳 – CoolShell
酷 壳 – CoolShell
GbyAI
GbyAI
F
Fortinet All Blogs
T
ThreatConnect
S
Schneier on Security
罗磊的独立博客
Y
Y Combinator Blog
C
Check Point Blog
T
The Exploit Database - CXSecurity.com
宝玉的分享
宝玉的分享
aimingoo的专栏
aimingoo的专栏
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
I
Intezer
F
Full Disclosure
T
Troy Hunt's Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
WordPress大学
WordPress大学
Application and Cybersecurity Blog
Application and Cybersecurity Blog
V
V2EX - 技术
C
Comments on: Blog
T
Tenable Blog
Project Zero
Project Zero
H
Help Net Security
A
Arctic Wolf
Google DeepMind News
Google DeepMind News
NISL@THU
NISL@THU
博客园 - 【当耐特】
F
Fox-IT International blog

DEV Community

Building an MCP server so Claude can query my SaaS analytics directly Google I/O 2026 and the Rise of the AI Ecosystem CV vs Resume: What's the Difference and Which Do You Need? student Devs: Build AI Agents & Compete for $55K in Prizes 🚀 How to Write a Cover Letter That Actually Gets You Interviews Battle-Tested: What Getting Hacked Taught Me About Web & Cyber Security Unda folders za kuandika code >> mkdir src >> cd src >> mkdir controllers database routes services utils >> cd .. Directory: C:\Users\mwaki\microfinance-system Mode LastWriteTime Length Name Code Coverage .NET AI slop debt" is technical debt on fast forward. Nobody's ready. Multi-Head Latent Attention (MLA) Memoria - A Local AI Reading Companion Powered by Gemma 4 Stop Trusting Your Accuracy Score: A Practical Guide to Evaluating Logistic Regression Models Serious Question: Is the Developer Job Actually in Risk Due to AI? published: true tags: #discuss #career #ai #help rav2d: We ported an AV2 video decoder from C to Rust — here's why Your New Domain's First Week of GA4 Is a Lie: 4 Days of Raw Data from a Launch Gemma Guide - Real-Time Spatial Awareness for Blind Users From YAML to AI Agents: Building Smarter DevOps Pipelines with MCP A Field Guide to Human–AI Relations (For the Newly Bewildered Mortal) The AI Agent That Learns While It Works — A Complete Guide to Hermes Agent Inviting collaborators to work on ArchScope ArchScope is an interactive web-based tool that lets you design, visualize, and test system architectures with real-time performance simulations. Github - ArchScope is an interactive web-based tool that lets you Gemma 4: Google's Open-Weight AI Is a Game Changer for Developers Confessions of a Git Beginner: Why the Terminal Stopped Scaring Me Docker 容器化实战:从零到生产部署 🚀 I Built a Full Stack Miro Clone with Real-Time Collaboration using Next.js Building an African Economic Data Pipeline with Python, DuckDB & World Bank API llms.txt vs robots.txt vs ai.txt: The Developer's Cheat Sheet Intigriti Challenge 0526 Writeup Business Logic Flaws: How Attackers Skip Steps in Your App to Get What They Should Never Have Why Vibe Coders Need Boilerplates to Save Time, Tokens, and Build More Secure SaaS Projects Idle Cloud Cost Is the New Egress Cost Quark's Outlines: Python Traceback Objects Ghost in the Stack (Part 1): Why uninitialized variables remember old data Building a High-Performance Local Chess Assistant Extension with WebAssembly Stockfish and Manifest V3 Breaking the Trade-off Between Self-Custody and Intelligent Automation on the Stellar Network I Open-Sourced a Practical Fullstack Interview Preparation Repository (React + Node + System Design) 🚀 How I Started Coding as a Student (Beginner-Friendly Guide) WordPress vs. Ghost: Why Automated Bot Attacks Are Making us think much I tested 4 AI agent-governance tools against an open spec - here's the matrix zkML Inference Proof: What the Receipt Proves, and What the Model Still Does Not I Scored 1000/1000 on AWS Certified AI Practitioner (AIF-C01) Here's Every Resource I Used Go - Struct and Interface Handling JSON Requests in Go Storing Kamal secrets in AWS Secrets Manager and deploying to a cheap Hetzner VPS How I Caught and Fixed an N+1 Query in My Django REST API I got tired of paying $10/month to remove image backgrounds – so I built it for free How to Start Coding as a Student: A Complete Beginner’s Guide 🚀 Storing Kamal secrets in AWS Secrets Manager and deploying to a cheap Hetzner VPS What Are Buffers? Build AI Agents with Hot Dev The Client Onboarding Checklist That Prevents 90% of Project Problems Scalable Treasure Hunts Are a Myth, But We Almost Made One Gemini 3.5 Flash Has a 1M Token Context Window. Here's What You Can Actually Build With It. I built a ultra-polished developer portfolio template using React & Tailwind v4 (with zero-JSX configuration) Gemini CLI Is Dead. Here's the Better Thing That Replaced It Post-quantum cryptography for embedded and IoT: secure boot, TLS and OTA Understanding Optimistic Preloading in Modern Applications Nobody Wants to Read Your Code (And You Don't Want to Read Theirs) A clothing pairing app E2B vs E4B vs 31B Dense: The Practical Guide to Choosing the Right Gemma 4 Model I built an AI app store screenshot generator because Figma made me cry — looking for brutal feedback Hello DEV Community — My Developer Journey Begins Adaptable apps on ChromeOS: a post-mortem The WordPress Paradox: Why It’s Here to Stay (and How to Stop Ruining It) I built a local voice AI that can change to 9 different personalities! UXRay: I Built an AI That Roasts Your UI Like a Senior Designer Would Wyrly DI: Type-safe Dependency Injection for Modern TypeScript The contract is the interface: agent-driven Steampipe Stave in one command Gemma 4's Hidden Superpower: Why Built-in Thinking Tokens Change Everything for Evaluation Tasks ⚡ WordPress Performance: The Real Truth They Don't Tell You A Mobile App Usually Needs an Admin System First Customer Portals Should Remove Repeated Admin Work Episode 4: The Time Loop (Layers & Caching) I Built ContextForge with Gemma 4: A Project Memory Generator for Developers and AI Coding Agents Why shadow DOM beat iframe for inline tooltips HOW TO CREATE USER AND ASSIGN ROLES IN AZURE WITH ENTRA ID When AI Blackmail Goes Viral Episode 3: The Secret Scroll (The Dockerfile) Monte Carlo Simulation for Engineers: Turning Uncertainty Into Numbers The tokens-per-byte trap: character-level 'compression' adds tokens Nobody Reads Your Code Anymore Why I built a collection of 5 free, zero-signup career finance tools for solo builders 🚀 New React Challenge: Instant UI with useOptimistic Resolvendo a Alucinação da IA na Arquitetura de Software com Code Property Graphs e .NET 9 S1 — Clean Backtrace Crashes: How to Diagnose and Fix Them Cómo solucionar el bucle infinito en useEffect con objetos y arrays The Brutal Reality of Running Gemma 4 Locally I made Claude Code refuse to write code unless the ticket scores 80/100 I Fed React's Entire Hooks Transition History to Gemma 4. Here's What It Found That We Missed. Building a Private RAG System: Lessons from a Local-First AI Journal CodePulse AI — Reviving an AI-Powered Repository Intelligence Platform How to Split Video into Segments with FFmpeg (CLI + API) I've audited dozens of estate agency websites. The same 5 problems show up every single time. Part 1: Taming Asynchronous JavaScript: How to Build a "Mailbox" Queue Building My AI-Powered VS Code Extension 🚀 Google Login in Express with PassportJS & JWT Great example of Gemma 4 moving beyond chatbots into real-world decision support. Using AI to guide everyday actions like recycling shows how impactful applied LLMs can be when designed for usability, not just capability. #Gemma4 #AI #Sustainability Building a Production AI Chatbot for an Educational Institute: Architecture, Lessons & Full Stack Deep-Dive Google Login in Express with PassportJS & JWT How I reclaimed 47GB on my MacBook by cleaning developer project junk Operators Are Not Oracles: How We Learned to Stop Worrying and Love the Configuration
How do you verify GitHub contributions without trusting self-reported skills?
Alex · 2026-05-23 · via DEV Community

I've been thinking about a problem that doesn't get talked about enough in hiring: the gap between what someone claims about their work on linkedin and what they actually did.

Anyone can list "open source contributor" on their resume. Anyone can paste a GitHub repo URL in a portfolio. But without looking at the actual commit history and contributor data — you have no idea if that person wrote 80% of the codebase or merged one typo fix three years ago.

So I started building a system to verify this properly. Here's what I learned — without giving away the methodology we use, because honestly, the moment you publish your exact algorithm, people optimize for it rather than actually doing the work.

The naive approach fails immediately

The first instinct is to just check if the person's GitHub handle appears in the contributor list. Simple, right?

Not quite. Three problems come up immediately.

People have multiple GitHub accounts. Work account, personal account, old account from college. A developer might have significant contributions spread across two or three handles. Checking one handle misses the full picture.

Contribution depth varies wildly. Being listed as a contributor could mean 2,000 commits or 1 commit. The contributor list alone doesn't tell you which. You need actual commit counts per author to understand the depth of contribution.

Public repos can be submitted by anyone. I can submit any famous open source repo to a portfolio system and imply I contributed to it. Without verifying my actual handle against the contributor data, the system has no way to know if I wrote the core architecture or just starred the repo.

What actually works — the principles

I'm not going to share the exact scoring formula. But I can share the principles that make verification meaningful.

Verify account ownership first

Before you can verify contributions, you need to verify identity. The only reliable way to confirm someone owns a GitHub account is OAuth. When someone authenticates via GitHub OAuth, you get a cryptographic proof of ownership — not a claim.

This is the identity anchor. Every contribution check runs against verified handles only. No claims accepted.

Handle the multi-account reality honestly

Developers legitimately use multiple GitHub accounts. A good verification system needs to support this — each additional account verified through its own OAuth flow.

The critical constraint: one GitHub account should only be linkable to one professional identity. Otherwise the whole system can be gamed by linking someone else's high-signal account to your profile.

This requires exclusive handle claiming. First claim wins. If a handle is already associated with another profile — it's blocked. No exceptions.

Contribution depth matters more than presence

There's a meaningful difference between someone who authored 40% of a codebase and someone who fixed a typo. Both show up in the contributor list. Only one actually shaped the project.

The verification system needs to reflect this distinction. Not all verified contributions are equal. Depth matters. History matters. Consistency over time matters more than a spike of activity.

Unverified doesn't mean worthless — but it means discounted

Not everything can be verified through OAuth. Public repos, old contributions, work done under inaccessible accounts — these are real but can't be fully verified.

The right approach isn't to ignore unverified sources. It's to discount them heavily and label them clearly. A user should always know what's verified and what isn't. A recruiter should always be able to see the difference at a glance.

Transparency about what can and can't be verified is more credible than pretending everything is confirmed.

Gaming prevention is architectural, not cosmetic

If your verification system can be gamed by submitting famous repos you didn't write, it's not a verification system — it's a vanity metric generator.

The aggregation rules matter as much as the scoring rules. How multiple sources combine, how unverified sources interact with verified ones, how the system handles edge cases — these decisions determine whether the final score means anything.

We've spent a lot of time on this. The details stay internal.

What this doesn't solve

No verification system is perfect. Worth being honest about the limitations.

Commit squashing — some teams squash all PRs into single commits before merging. A developer who wrote 40 separate commits might appear as 1 in the contributor list.

Pair programming — code written together often gets committed under one person's handle. The other person's contribution is invisible to the API.

Private repos — everything above works for public repos. Private repos require broader OAuth scope, which is a bigger ask for users.

Old accounts — significant contributions under an account you no longer have access to can't be verified without OAuth on that account.

These are real limitations. A verification badge isn't a guarantee — it's evidence. The weight of that evidence depends on the depth and breadth of verified sources.

Why this matters now

LinkedIn profiles are self-reported claims. AI writes perfect ones in 30 seconds. Endorsements come from people who've never seen your code. The entire professional identity system is built on statements that cost nothing to make and nothing to fabricate.

GitHub commits are different. A three-year commit history with consistent cadence, real collaborators, and downstream ecosystem impact — that can't be generated by a chatbot. That's real signal.

The question is how to surface that signal in a way that's portable, shareable, and resistant to gaming. That's the problem worth solving.

Where this is heading

I've been building this verification logic into a larger system called Warrant — a proof-of-work portfolio that computes verified scores from GitHub signals rather than letting engineers describe their own skills.

The exact methodology stays opaque — intentionally. The moment you publish the formula, people optimize for the formula instead of doing real work. We'd rather be the PageRank of professional identity than the ATS keyword game.

If you're an engineer curious to see what your verified GitHub signals look like, you can try it at warrant-plum.vercel.app. Free, currently in beta, no credit card.

If you've thought hard about contribution verification — I'd genuinely like to hear what edge cases you ran into. The ones I listed above are the ones keeping me up at night.