#CI
200
2026-10-19
Show HN: Sphinx – A hook that quizzes you on your AI's code before shipping
A
FOSS, Basically it plugs into your existing coding agent workflow and every time you push to prod it'll throw up a questionnaire that checks if you understand how the code you're pushing works.
2026-10-13
Show HN: Chkit – Schema, migrations and backfills for ClickHouse (like Drizzle)
B
Hey HN, im Marc, co-founder of ObsessionDB. We are open sourcing ChKit, our tooling to manage schemas, migrations and backfills for clickhouse. I am a big fan of the type safety drizzle provides for the database. Manage the schema in typescript and generate migrations from it is a powerful workflow. I always wished something like it would exist for clickhouse, so we could manage our analytical workloads the same way. It didn't exist, so we build it. We build it after running ClickHouse at petabyte scale in our previous company, were we managed hundreds of tables, MVs and endpoints reading from them. The way it works: 1. You define your schema in typescript, with typed helpers for tables, mv, column types etc.. 2. You generate the migration, that contains the DDL, to get your clickhouse instance from status quo to what your current typescript schema defines 3. Your CI can check for drift 4. You run the generated migration against production 5. You use the defined types in your code, to ingest your data while making sure it has the correct type. Bonus: if your schema change was BC breaking, we generate the sequence on how to backfill the data, into the intermediate table to migrate (this is quite the hard problem with large tables and schema evolution) In case you have already a clickhouse instance with a schema, you can pull it down and start using ChKit from where you are. Run our generator to setup the boilerplate: npm create chkit@latest If you folks are running clickhouse in production, I am curious to hear what other challenges you are running into.
2026-09-29
kofiadeyemiq/action-dist-verify
A
Rebuild the JavaScript GitHub Actions your workflows pin and check that their committed dist matches the source.
2026-08-24
Reality-JH/frontend-promotion-guard
B
Release gate for CSS integrity, computed styles, visual regression, and safe Docker promotion.
2026-10-14
MrLouisWright/csp-forge
A
Scan a built static site (dist/, build/, out/) or live URL and generate a tight Content-Security-Policy with sha256 hashes for inline code. Outputs header, meta, Nginx, Apache, Netlify, Vercel, Helmet, JSON; --check mode for CI.
2026-11-09
brunnojob/cifuse
A
Turn noisy CI logs into grouped failures, exact evidence and investigation steps. Offline CLI, reusable GitHub Action and bilingual browser workbench. No API keys.
2026-10-06
uzairansaruzi/p3-stack
B
pstack reworked for T3 Code: delegated subagents, worktree threads, PR watching, scheduled runs.
2026-09-15
pliablepixels/gap-trap
B
Turns vibe coding into high quality code. Sets up rules and gates in your repo so AI-written code stays correct without you reviewing every line.
2026-09-10
senoff/self-hosted-ci-runner
A
Stand up self-hosted GitHub Actions runners on one box, provisioned so heavy CI jobs don't OOM or fill the disk (per-runner swap/scratch + reaper). Parameterized; Hetzner reference config included.
2026-11-09
faissalrez/svelte-check-reporter
A
Show svelte-check's Svelte and TypeScript errors in GitHub pull requests and GitLab merge requests: Code Quality reports, Actions annotations and SARIF for code scanning.
2026-10-24
theorem-labs/oss-verify
A
OSS Verify: enrollment and build instructions for formally verifying open-source fuzz targets
2026-09-27
agentscope-ai-java/deno-lockfile-diff
B
Turn a deno.lock diff into prioritised supply-chain signals — new raw-URL imports, integrity changes, registry moves.
2026-09-18
planetscale/lead
B
A non-production Postgres text-search extension for exercising TIN-compatible application SQL in development, test, CI, and staging environments
2026-09-23
mizchi/jev-test-filter
B
Score every test against a git diff with Jev, and emit the filter arguments vitest, node:test, Playwright, cargo test and go test already understand
2026-09-06
byJoey/warp-masque-actions
B
GitHub Actions automatically generates Cloudflare WARP (MASQUE) keys and mihomo configs, with artifacts stored only in artifacts
2026-10-14
MrLouisWright/header-sentinel
B
CI-friendly CLI and API that fails builds when deployed URLs are missing or misconfigure HTTP security headers (HSTS, CSP, COOP, cookies...) with specific fixes. JSON & SARIF output.
2026-08-29
jameskomo/config-drift-checker
B
Config Drift Checker for coding-agent setups: CI for your Claude Code configuration (CLAUDE.md, skills, hooks) — eval cases, release-watch, regression alerts
2026-10-15
jburgess-r7/CVE-2026-97229-PoC
B
GitLab CI lint integer-overflow RCE PoC for CVE-2026-97229, validated against the official 19.4.1 CE amd64 image
2026-08-29
k1LoW/gh-share
B
gh-share is a GitHub CLI ( gh ) extension for sharing a single HTML file or other files and directories using GitHub Actions artifacts.
2026-10-04
tools4imps/exhale-ruby
B
The contraction gate for Rails: no PR merges while the codebase holds duplication the Contract doesn't keep
2026-10-14
Show HN: Deslop – Oxlint rules for AI-generated TypeScript
C
Catches unsafe types, duplicate code, and low-value tests.
2026-10-28
lichenlang89/dn64
B
DN64 dual-stack experimental network registry | RPSL-style objects, signed PRs and automated validation
2026-08-28
open-daimax/daimax-appbench
B
An automated benchmark platform for AI-generated apps — built-in evaluation rules, standard sample sets, and layered test cases across a multi-dimensional metric system. One pipeline runs build, install, E2E tests, and scoring into a shareable report.
2026-10-05
MatteoGabriele/interlinked-action
B
GitHub Action that flags agent-written PR descriptions
2026-10-15
tinyhumansai/openscion
B
OpenScion is an open-source, server-centric source control system for very large monorepos where most clients are AI agents and CI jobs rather than people on laptops. Based on Anthropic's Scion
2026-10-25
mokevnin/dev-guardrails
C
An opinionated, curated list of tools for enforcing software development standards: one recommended tool per job, with limits.
2026-10-12
DosX-dev/TinyCC-builder
C
Build the latest TinyCC for Windows with one click. Complete portable x64/x86/ARM64 toolchain, full WinAPI headers, automatic releases.
2026-10-27
codician-team/diffinery
C
Open-source, agent-first GitHub and GitHub Actions alternative that runs on your own Cloudflare account: git hosting, pull requests, code review and drop-in GitHub Actions YAML on Workers, Durable Objects, R2 and Containers.
2026-09-29
upgundecha/awesome-cloud-emulators
C
A curated list of cloud emulators and local cloud development tools for AWS, Azure, and Google Cloud. Explore LocalStack, Moto, Azurite, Firebase, and more for integration testing and CI/CD.
2026-09-21
mitkox/esf
C
Self-hosted engineering software factory: Temporal, CubeSandbox agents, deterministic verification and durable evidence. MIT-licensed Machinist fork.
2026-09-27
PinoyFreeCoder/deployment-checklist
C
Language-agnostic pre-deployment checklist for web & mobile apps — security-heavy, with human and AI-agent versions.
2026-09-20
ThisTakou/UserAgent-list
C
Automated User-Agent database for 100+ browsers on 100+ operating systems. Updated every 5 minutes via GitHub Actions. Weighted by real-world popularity, grouped by OS and browser, with a cumulative ALL/ folder of unique agents.
2026-10-04
Zhou-Yujing114514/deepseek-harness-linux
D
First-class Linux packaging for DeepSeek Harness desktop — AppImage, .deb, .tar.gz for x64/arm64, built by native CI.
2026-10-14
cromford-ai/cromford
C
Cromford: the open-source software factory. Tickets in, reviewed, merged and production-checked changes out.
2026-08-31
KrisTHL181/Break-This-Repo
C
This repository automatically merges pull requests without conflicts. All text is subject to edits via PR and shouldn't be trusted.
2026-08-25
bashebr/ai-native-sdlc
C
AI-native SDLC workflow as a reusable Codex and Claude Code skill and plugin
2026-10-14
grandamenium/agent-software-factory
C
How to build a software factory: verification you trust at the scale of hundreds of agents and PRs
2026-10-09
just-be-dev/effect-cloudflare-foldkit-template
C
Reusable organization, tooling, and guardrails for Effect 4, Foldkit, Bun/mise, and Alchemy 2 on Cloudflare
2026-10-13
jiayx/d2r-mobile-build
D
GitHub Actions builds for jhaizhou-ops/d2r-mobile. iPhone/iPad IPA and game resources in Releases.
2026-10-14
ahmadjawad533/90-days-of-cloud-engineering
D
Free 90-day cloud engineering roadmap: Linux, Python, AWS, Docker, Kubernetes, Terraform, CI/CD and security, with hands-on labs and a capstone project. Go from zero to job-ready. AWS free-tier friendly.
2026-11-05
Magmazumsignify/qa-delivery-check-12d035
D
Temporary acceptance-test repository for delivery checks
2026-11-08
fawudaozhubaoqin/sbt-scala-multiproject-template
unrated
SBT Scala multiproject template with initial configuration
2026-11-07
brunnojob/patchscope
unrated
Local-first Git diff triage. Turn patches into actionable review checklists in your browser, CLI or GitHub Actions. Zero dependencies, no AI keys, no uploads. By brunnodev.
2026-11-06
Sarthzk/internship-tracker
unrated
Auto-updated tech internships in India from 160+ company career pages, with Telegram alerts. Serverless on GitHub Actions.
2026-11-05
kunchenguid/runner-up
unrated
GitHub Actions runners on your own machines, one fresh container or VM per job. Completely eliminate your cloud CI bill.
2026-11-05
MichaelCade/90DaysOfDevOps
unrated
This repository started out as a learning in public project for myself and has now become a structured learning map for many in the community. We have 3 years under our belt covering all things DevOps, including Principles, Processes, Tooling and Use Cases surrounding this vast topic.
2026-11-04
MicTx/spec-harness
unrated
Task-package workflow tool for AI coding agents, managing long-term changes with verifiable scope, evidence, and Git gates. (Task-package workflow for AI coding agents with verifiable scope, evidence, and Git gates.)
2026-11-03
GlobalArtInc/astrum-repository
unrated
Self-hosted artifact repository manager written in Rust. Hosts, proxies and groups 30+ formats: Docker/OCI, Maven, npm, PyPI, Cargo, Go, Helm, NuGet, Hugging Face, Terraform and more. PostgreSQL for metadata, blob stores on disk or S3. An open-source alternative to Nexus and Artifactory.
2026-11-01
justxor/devops-interview-2026
unrated
Cheat-sheet course for preparing for the DevOps 2026 interview: Linux, networking, Docker, Kubernetes, CI/CD, Terraform, clouds, SRE, 150 questions
2026-10-30
dgesteves/onsystem
unrated
Keeps coding agents on your design system: catches palette colors, native elements and APIs your system lacks, at every edit and pull request, with the fix. Set it up once in your design-system package; every app in your monorepo gets it.
2026-10-30
github/lever
unrated
Copilot skills for building feedback loops, delegating safely, and moving repeatable work into automations.
2026-10-30
sanjayadanushka712/TaskFlow
unrated
End-to-end DevOps TaskFlow API — FastAPI, PostgreSQL, SQLAlchemy, Alembic, Docker Compose, Pytest and GitHub Actions CI,Kubernetes,prometheus,Grafana
2026-10-27
fzakaria/rewindvm
unrated
Deterministic Linux VMs you can scrub, rewind and fork. Find and replay flaky builds and tests.
2026-10-26
SivaSaiKrishnaSuryadevara/docker-ci-gatekeeper
unrated
Self-healing Docker CI: BuildKit failure taxonomy, Claude Code fixes, rebuild verification, capped retries.
2026-10-26
mokevnin/dev-quality-gates
unrated
An opinionated, curated list of tools for enforcing software development standards: one recommended tool per job, with limits.
2026-10-26
winnin/farol
unrated
Know the risk of merging a pull request, and where it lives. Free, open-source CLI and GitHub Action: after your AI review, farol shows the riskiest files, what they reach, diff coverage and contract breaks. TypeScript/React, Go, Python.
2026-10-21
Show HN: PatchWave - Add static analysis and automerge to Dependabot
unrated
Hey Hacker News, we're Ben, Josh, and Donnie, co-founders of PatchWave. PatchWave is a GitHub App that combines static analysis and eval'ed agents to analyze and (optionally) auto-merge PRs it deems as safe. If a Dependabot PR breaks your CI build, a fix agent works to get CI passing again. Dependabot PRs suck. Nobody likes dealing with them. Most of the time they go ignored or a senior engineer spends their valuable time dealing with them. Before PatchWave, I ran a freelance business charging clients hourly to do exactly this kind of "keep the lights on" work. Even at our small startup, we'd spend Monday mornings dealing with Dependabot PRs. Having a human-in-the-loop working with an agent on these PRs was time consuming and, often, agents would get lazy and not actually validate how an upstream change affected the codebase. And, as the quantity and severity of CVEs increases, merging security updates quickly becomes increasingly important. PatchWave is a set of specialized agents that uses static analysis tools on context we gather deterministically. 1. We pull the changelog, the code diff between versions, security advisories, and CI results. 2. The agent checks out your code in an isolated sandbox, where it uses structural code search, type checkers and your project's own toolchain to understand how your codebase uses each dependency being updated. Every Dependabot PR gets a report. You can see a few examples (against OSS repos) here: https://reports.patchwave.ai/alam00000/bentopdf/pull/913 and https://reports.patchwave.ai/shipshapecode/shepherd/pull/355... 3. If CI fails, we automatically dispatch a fix agent to try to get CI green again. For most PRs, this means updating your code to use a newer API, fixing linting/formatting issues, etc. 4. We have an optional feature that allows auto-merging certain PRs when PatchWave deems them as safe and the PR aligns with your auto-merge policy. Our recommended auto-merge policy is to auto-merge patch/minor/major dev dependencies and patch/minor production dependencies. You can customize this policy or turn auto-merge off entirely. PatchWave will skip auto-merge in a bunch of cases where a human should review. For instance, if provenance changes (e.g., a package that's usually published by GitHub Actions via Trusted Publishing is suddenly published by an API Key), we require human review before merging. Dependabot also instituted an on-by-default 3-day cooldown to reduce the risk of supply chain attacks. If PatchWave makes any changes via a fix agent, we'll always require your review before merge. Currently, PatchWave only works with Dependabot and GitHub. We plan to offer Renovate support in the future. We've eval'ed the agents the most against TypeScript and Ruby, but are always adding to our eval suite to improve accuracy. The fix agent works best with PRs that require modest code changes. For large updates, especially updates that span multiple majors, our fix agent will give up and provide you a remediation plan to help you mitigate. On the privacy/security side of the house, our SOC 2 Type II audit is in progress (see trust.contextbridge.ai). We only run on repos you select, our agents run in a short-lived microVM per run, we use Amazon Bedrock with zero-data-retention, and never train on your code. We're offering 25 free PRs per GitHub org, per month with no credit card required. Additional PRs are billed at about $1/PR, with discounts for higher volume. We also would love to accelerate OSS projects, so reach out to ask about additional free credits. If you hate dealing with Dependabot PRs, we'd love for you to give it a shot and tell us what you think. Josh, Donnie, and I will be around answering any questions and responding to any feedback you have.
2026-10-21
Show HN: Git-Zmarshal
unrated
Orchestrating build trains for many concurrent agents, on top of git.
2026-10-20
Show HN: PredixLab – my personal system to discover investment opportunities
unrated
GitHub predixlab/predixlab-infra ★1
2026-10-19
aarondfrancis/fleet
unrated
macOS app for a fleet of GitHub Actions self-hosted runner machines on a tailnet
2026-10-17
arla6ka/design.how
unrated
Agent skills and design systems from design.how. Build a design system from your app, use agents to ship UI, enforce it in CI.
2026-10-16
Akimiya-z/codex-guard
unrated
Quality gate for AI/Codex-generated pull requests: blocks TODO leftovers, leaked secrets, sloppy commits and red CI before they reach main.
2026-10-16
coldteadotai/pr-lens
unrated
Review code 100X faster. Lens draws every PR as animated architecture and data-flow walkthroughs, inside the pull request itself. Use it as a GitHub App, GitHub Action, CLI, or a Skill for your coding agent
2026-10-16
coleam00/ai-software-factory
unrated
You plan the release, the factory builds it, you test it in staging. GitHub issues in, independently reviewed and merged pull requests out, all on Archon workflows.
2026-10-16
lubin776/tvbox-api-backup
unrated
TVBox API automated backup project, including interface scraping, live source aggregation, static frontend navigation, built on Python + GitHub Actions, fully externalized configuration.
2026-10-16
snakyvine/codex-maintainer
unrated
Evidence-grounded issue triage, pull request review, and release notes for GitHub maintainers. CLI + GitHub Action.
2026-10-16
tetrionlabs/mathema
unrated
Claim-Driven Development: turn software intent into verifiable evidence.
2026-10-10
Show HN: Fabrika, Opinionated Software Factory
unrated
I built a software factory that focuses on delivering production ready code and making it as easy as possible for humans to underwrite that code. It's a very early version, but I would love feedback.
2026-10-09
Show HN: LLM Fuzz CI
unrated
Hi HN! Most of the explanation is in the blog post, and the code lives there: https://github.com/tiime-software/llm-fuzz-ci/ Happy to receive feedback, and to know how other people use agents to improve code security!
2026-10-09
Show HN: ScreenCI – Tutorial videos as E2E tests, written by your coding agent
unrated
Hi HN, I'm Olli. My friend Patrik and I are bootstrapping ScreenCI: tutorial videos of your web app that you can re-record in your CI on every release. If the video is out of date, the run fails like any E2E test. I've been on teams where the tutorial videos were outdated, or even where we held back UI improvements due to manually maintained videos. That's why we built system where you can describe the videos as Playwright E2E test code. Coding agents are very good with writing tests and you can run these scripts against your app on your machine. ScreenCI converts them into narrated, auto-zoomed, subtitled videos. The recording and its timing data are uploaded for rendering, your source code and browser session stay local. The CLI is MIT ( https://github.com/screenci/screenci). Browser video previews are free with no account. GPU rendering and video hosting are a paid service. Try it on your app or example demo SaaS https://demo.screenci.com. I'd especially love feedback on whether treating tutorials as executable tests makes sense to other teams, and how you currently keep product videos up to date.
2026-10-07
Show HN: Counterbranch – See how your PR changes access control
unrated
Hi, we just released Counterbranch as a GitHub Action (alpha) and are looking for feedback. The action scans your codebase looking for unintended changes to authorization. This can happen in custom code, endpoints, guards, rbac, abac, policy-as-code files, etc. and can lead to broken access control or data exposure. The scanner doesn't use LLMs and is blazing fast. The results show up as a comment on each pull request so you can maintain and improve authz for any volume of human and agentic coders.
2026-10-06
Show HN: Self-bench – benchmark coding agents on real-world software
unrated
Hey HN, Today, we're launching selfbench.dev, an open-source tool that lets you create and run evals automatically from your PRs. Every benchmark with sufficient trust eventually gets benchmaxxed (Goodhart's law) - the labs are incentivized to maximize their scores on that benchmark, which isn't predictive on whether it'll actually work within your setup. This has been a time-consuming process that only the largest companies can afford to do, so we built self-bench to fix this. Self-bench uses agents to author / review Harbor environments generated from your PRs. You then approve every eval that the agent created, and can model/harness evals concurrently on sandboxes. To save you money, we also allow you to connect your OpenAI and Claude subscriptions so you don't have to pay raw token costs. We ran evals on several large codebases like - Posthog ( https://selfbench.dev/PostHog/posthog) - Next.js ( https://selfbench.dev/vercel/next.js) - Sentry ( https://selfbench.dev/getsentry/sentry) - Pi ( https://selfbench.dev/earendil-works/pi) - as well as other fantastic open-source projects (all on selfbench.dev) From our evals: - Kimi K3 and GLM 5.3 are almost always more expensive, yet less performant than models like GPT-6.1 Sol and Claude Opus 5.5, due to token efficiency. - GPT-6 Luna is almost always the most effective "cost-efficient" model we've tested, not open-source models. We'd love for you to try this on your codebase and let us know what you think!
2026-10-03
Show HN: Run Google DataProc cluster on your local
unrated
Google does not provide official docker image for developers or AI agents to run dataproc cluster locally. so everybody need to spin up for even dev/CI testing,etc.. now you or your AI agent can: docker run --rm agentcloud/dataproc:3.0.0-debian13 self-test saves time and cost. it basically packages the same component version and make the hadoop and spark to developer. Here are docker images for other dataproc versions: https://hub.docker.com/r/agentcloud/dataproc/tags here is full blog for more use-cases: https://local.cloud/blog/run-dataproc-locally-docker/
2026-10-03
Show HN: Levenshtein – Curated Go lint rules and CI checks
unrated
Hey HN, I've been recently building a lot of Go projects and noticed myself setting up lint rules and CI/CD and starting from scratch each time. Also, if I found a good deterministic check to use in one repo, I'd have a hard time putting that in my other repos. So I built Levenshtein ( https://github.com/wangjohn/levenshtein). It's a curated set of Go lint rules and verification checks that run locally and in CI. The rule set is pretty comprehensive and builds on Staticcheck and other existing analyzers, with some additional rules of my own. It includes: - Go vet - Staticcheck - Modernize - Bug finding analyzers - Vulnerability / security analyzers There's also some fun optional checks that you can configure like: - Semantic linters using Jev - Race detectors - Mutation testing for tests - and many more! I've been hooking it up to my own projects and caught dozens of bugs already. For example, one finding was a test that simulated database changes with os.WriteFile but ignored whether the writes succeeded. Would love feedback, particularly about the default rules and what should be default/what shouldn't!
2026-10-01
Show HN: SFML – A markup language for software factories, Terraform for agents
unrated
SFML is a language specification for defining software factories. You can think of it as Terraform for your software development lifecycle. I started from a language spec to help think through both how a factory is defined and how a conforming runner processes it. The push to do this comes from leading teams where everyone has a unique coding setup, which results in different agentic coding processes. People also want to work together on improving that process. Right now they do it through shared AGENTS.md files and, in some cases, committed Claude and Codex settings files. But it hasn't led to the collaboration we all want. SFML is my attempt to help make that happen. My core bet is that the Unix philosophy applies to agentic coding just like it applies to all other coding: small steps with clear inputs and outputs, composed together to get results. Most agentic setups lean on ever-growing AGENTS.md files that quickly become unwieldy. Breaking them up helps, but then the agent has to rediscover and reassemble your process on every run. I'm pretty early in thinking about what SFML should be, and I'm hoping to hear from dissenters and collaborators here today, to push me to think more critically and to show me directions I haven't imagined yet. Thanks in advance for your feedback.
2026-09-30
Show HN: A terminal UI for GitHub Actions across all repos and orgs
unrated
We have many repos across multiple GitHub organizations (no monorepo yet). I needed a tool to list and manage Actions from the terminal instead of clicking through the GitHub web UI, so I made this. Hope it's handy.
2026-09-29
Show HN: Assay – a QA CLI that finds bugs with no LLM and no tests written
unrated
I've always found it odd there was no deterministic QA tools with zero baseline needed, especially after so long. It's always been either (1) playwright or cypress that require written tests, dependant on the tests YOU write, or (2), asking the LLM to find and test bugs in your code, which has 2 cons, its costly (sometimes), and its non-deterministic. That's why i built assay. Its only dependencies is playwright & chromium, and you point it at any folder with a webpage and it runs tests on its own by driving the webpage itself in a browser and clicking every control. It then flags anywhere the webpage contradicted/disagreed with itself; it doesn't know right from wrong NOR what the webpage is about, but universally, a page disagreeing with itself is almost always a bug. An example of this is on a paint app, if you draw two strokes on a canvas and click undo twice, you expect them both to undo each stroke sequentially; in one of 225 benchmarks, clicking the undo the first time didn't remove the first stroke, and only the 2nd click worked. assay drove that and caught it. As for benchmarks, there are 2 variants that are all reproducible in the repo. The first is 225 generated web pages that were first checked by hand, then had assay run on them. There was a total of 20 bugs across all programs, and assay caught 15 with the right reasoning, and had 0 false failures. The second was a harder one where an LLM planted 5 bugs across 10 working original webpages. assay found 12 of the 50 and had 0 false failures, which may seem low, but assays superpower is that its cheap and quick. assays median runtime is 14s, and it plugs into 15 agentic coding harnesses with a skill, plus claude code and deepseek harness have their own plugin that automatically runs it with a stop hook every time the LLM touches a webpage. My favourite feature is that it groups flagged tests together if their of the same bug. More details are in the repo about this since this is getting a little long, but the links it makes have its own benchmarks, 51/51 links it got right with 0 false links. This serves as additional context to you, if you use it as a raw cli, or to your agent if your using it with an LLM harness. pip install assay-ui. All alternative methods to install are on the github, including harness support.
2026-09-28
Alpha-Park/genpark-semver-breaking-change-auditor-skill
unrated
Semantic versioning (SemVer 2.0) breaking change auditor inspecting AST public API surface diffs, parameter reordering, and removed exports.
2026-09-28
Show HN: LightCloud – A cloud console organised like file system
unrated
Hi HN, Light Cloud is a hosting platform where the unit of organisation is a folder. A folder holds everything project needs: frontend, API, database, env variables, preview per branch.
2026-09-21
Scoutnefreeze/git-release-manager
unrated
Automate versioning, changelogs and GitHub releases — semantic version bumps, tag creation, and release notes in one command.
2026-09-21
Show HN: Mini-Runbot – Ephemeral Odoo Enviroments Using Python and Docker
unrated
I build a Mini-Runbot, an open source PoC for creating ephemeral enviroments for Odoo from a Git commit. This is a mini implementation of the real workflow used by Odoo in Odoo-Runbot and the workflow using in the platform Odoo.sh This workdflow take a testing branch and prepare a database, install modules, start Odoo instance, export a port, check that everything works and cleaning everything up afterward. A build can: - resolve a Git branch or tag - prepare an isolated checkout - install selected Odoo modules - run Odoo test - start Odoo instance - test an HTTP healtcheck - expose a temporary preview - destoy the environment when it is no longer needed The project is written mainly in Python, using FastAPI, Typer and Codex. It is intentionally a small and single-host PoC, thats not a replacement for Odoo official runbot, I wanted to explore a lightweight preview environment platform. The applications is available on PyPI: pipx install mini-runbot Docs: https://rafnixg.github.io/odoo-platform-ephemeral-environmen... Source: https://github.com/rafnixg/odoo-platform-ephemeral-environme... PyPI: https://pypi.org/project/mini-runbot/ The next areas I am exploring are GitHub Pull Request integration, workers and job scheduling, observability, concurrency, and eventually distributed execution. I would especially appreciate feedback from people working with Python, Odoo, CI/CD, or Platform Engineering on the architecture and isolation model.
2026-09-19
Show HN: Free GitHub Action that scans PR diffs for malicious code, not quality
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I watched a video recently on malicious code injection into OSS repo PRs and how they can go undetected because of how well they're hidden and decided to do a project for this. This tool is essentially used in unison with ai code review bots like greptile. While tools like greptile reason because they run with LLMs, this is a deterministic step before greptile that scans for malicious code (command execution, credential access, exfil, auto-run hooks, obfuscation, and prompt injection; regex + semgrep, no LLM), then can trigger the ai code reviewer like greptile or coderabbit, pointing it to its findings. It's free/MIT and runs in your CI.
2026-09-18
RhythmFlamingoOutfit/git-release-manager
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Automate versioning, changelogs and GitHub releases — semantic version bumps, tag creation, and release notes in one command.
2026-09-16
Show HN: Local static analysis for coding agents
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Your agent can already check results on a PR, fix issues, and unblock a quality check. That’s useful. But you don't have to wait until a PR exists. With Codacy's new skill, when you're working with an agent like Claude Code, you can run an analysis locally and fix issues before the first push. There are two Codacy Skills as part of this launch: one teaches the agent how to set up and run Codacy analysis locally, and another one that teaches it how to use Codacy analysis as part of any code review. Walkthrough here: https://blog.codacy.com/introducing-codacy-skills-part-4-sca...
2026-09-14
dhtoan/AunoForge
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AI-assisted OSS maintenance you can verify — triage issues, reproduce bugs, review PRs, check regressions and security, and prepare releases with humans in control.
2026-09-12
Codeprojectingfuture/DevSecOps-Lab
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End-to-end DevSecOps Task Manager demonstrating automated testing, security scanning, containerization, monitoring, and cloud deployment.
2026-09-11
Codeprojectingfuture/DevOps
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CI/CD workflow for a Java Spring Boot application with automated testing, code quality analysis, containerization, and deployment automation.
2026-09-09
Show HN: Archprint, infer architecture lint rules from your repo's import graph
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This tool started as a research for me trying to answer the question "Does AI agents drift from your architecture conventions or if you need enforcement instead?". So I started out building a benchmark to test that premise and on the scope I tested, the agents did not drift and I had to stop that research line. So to reuse what I have learnt from that research, I started out trying to catch engineer's regressions through review and CI and create those conventions codebases already follows with the evidence instead of leaving them in someone's head. Before I started building this tool, I also mostly write the rules by hand and linter's documentations for every linter I wanted to use. But after my research, the tool automates the process and I'm excited to see how it can help other engineers too. I ran the full package workflow (scan, recommend) across 92,861 real public TypeScript repositories on github and it completed on every one without a single crash and the reversible install/uninstall round-trip held. I will appreciates any feedback you have on the rules it infers for your repo and how it can help you enforce them or not. The study is public here https://github.com/Tommkruix/agentrulebench and Archprint is public here https://github.com/Tommkruix/archprint also.
2026-09-08
Show HN: Archprint, infer architecture lint rules from your repo's import graph
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GitHub Tommkruix/archprint ★0 · Infers architecture rules from your TypeScript repo's real import graph, gates each on statistical evidence, and emits them into the tools you already use (ESLint, dependency-cruiser, ts-arch). Turns the boundaries your code already follows into enforcement, so architecture drift gets caught, not just documented. · Every TypeScript architecture linter makes you write the rules by hand (dependency-cruiser, eslint-plugin-boundaries, Sheriff, ts-arch). Archprint does the opposite: it reads your repo's real import graph, finds the boundaries your code already respects, and turns the ones that pass a statistical confidence gate into ready-to-install lint rules, with the evidence attached (how many files conform, how many break it, how confident the inference is). The framing that drove it: your CLAUDE.md / AGENTS.md is guidance; your lint rules are enforcement. Archprint generates the enforcement from patterns your codebase already demonstrates, so you adopt rules you can trust instead of hand-authoring them. It's deliberately honest about what it will enforce unattended. The mechanical families (no import cycles, production must not import tests, no console in library code, no undeclared deps, import style, public-API barrels, DB/UI-in-a-server-entry) had zero false positives across an adversarial correctness audit, so those auto-generate. The structural families (layer/role boundaries, UI/data separation) infer a "layer" or "role" from paths, which can be wrong, so they're held for human review by default. One wrong enforced rule costs more than zero rules. It emits into the tools you already use, ESLint (including a shareable one-file preset), dependency-cruiser, and ts-arch, so it complements your stack. Framework-aware across React, Angular, Vue, Svelte, Next, Nest, SvelteKit, Nuxt, and Remix. Before posting I ran the full CLI workflow (scan, recommend, generate, wire, eject) across 92,861 real public TypeScript repositories: it completed on every one without a single crash, and the reversible install/uninstall round-trip held. npm install --save-dev archprint npx archprint scan . Docs: https://tommkruix.github.io/archprint/ · Repo: https://github.com/Tommkruix/archprint Early (0.x). Feedback very welcome, especially on the rules it infers for your repo.
2026-09-07
Show HN: Wayfinder – A reference implementation for evaluating AI applications
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Testing is critical to software applications — first to make sure they reliably serve the purpose they were built for, and then to make sure they stay that way as they grow, evolve and change. The same applies to AI applications as well. But testing AI applications is very different from testing classic software applications, especially because of their non-deterministic nature. It is very important for AI Engineers to develop a deep understanding of AI Evaluation to be able to build reliable AI applications and ship changes faster without breaking their existing behavior. AI Evaluation is often presented as a long list of independent techniques: Rule-Based Evaluation, Human Evaluation, LLM-as-a-Judge, Offline Evaluation, Online Evaluation, Component Evaluation and End-to-End Evaluation. But in practice they all complement and build on each other. I built Wayfinder, a reference implementation where I explore these concepts progressively using the same AI application. My goal was to build an intuition for how the different evaluation techniques fit together, and how to turn them into an evaluation strategy for an AI application. I'd be interested to hear how others are approaching evaluation in production AI applications and what you think is missing from this implementation.
2026-09-04
alphaparkinc/genpark-pull-request-semantic-risk-blast-radius-scorer-skill
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Pull request semantic risk blast-radius & breaking change scorer (Qodo)
2026-09-03
Show HN: Terraplane: webhook-based Terraform PRs with runners in your network
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Terraplane lets you run Terraform from GitHub PRs against private networks without punching holes in firewalls. I built Terraplane after running in to the same problem for years: 1: I don't want the IaC pipeline to die when the server it's running on does. An all-in-one box is a single point of failure. 2: I don't want to bend my network around the tools I use. I'd prefer not to punch holes in firewalls or peer networks just so automation can reach what it's managing 3: Cross-account IAM/SA assumption isn't the same as direct network access A runner with cloud credentials can call a lot of APIs for sure. However many TF providers require direct access to the resource they're managing and role assumption often doesn't cut it. Terraplane is designed to address this. An orchestrator component runs somewhere you're happy for public traffic to reach. Webhooks hit the runner and it queues jobs for execution. Agents run inside your network and pull jobs from the orchestrator. They run TF plan/apply locally, and return the output to the orchestrator. Credentials for private services stay in the network they belong to. Terraplane is roughly designed to be ready to write integrations for SCM providers other than GitHub. I haven't done it yet, but it should be fairly trivial. This is an early alpha. I use it for my org's IaC pipeline and I've been happy with the results. I'm open to any and all feedback. I built this for me, I hope it works for you.
2026-09-02
alphaparkinc/genpark-automated-secret-detection-sast-security-gatekeeper-skill
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Automated secret detection & SAST security gatekeeper (GitLab SAST style)
2026-09-02
Show HN: Durable Workflow 2.0 polyglot workflows in PHP, Python and Rust
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I built a sample app for Durable Workflow 2.0 that lets you try it out via GitHub Codespaces in your browser. What makes DW 2.0 unique? Several deployment modes. If your app is Laravel then you can embed the workflow engine inside your app and it works with the storage and queues that your app is already using. No additional infra needed. If not then you can run it in service-mode which provides a language-neutral HTTP+JSON control plane. Under the hood, it's still a Laravel app so it's fairly simple to deploy. But you don't need to worry about PHP or Laravel in service mode for the most part. There are prebuilt Docker images and Helm charts. Check out the launch article: https://durable-workflow.com/blog/durable-workflow-2-0/ Feel free to ask me questions here.
2026-08-31
alphaparkinc/genpark-multi-tenant-gitlab-webhook-event-router-skill
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Multi-tenant GitLab webhook event router & CI/CD trigger (GitLab Webhook style)
2026-08-31
alphaparkinc/genpark-unified-gitlab-ci-pipeline-analyzer-optimizer-skill
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Unified GitLab CI pipeline analyzer & stage optimizer (GitLab CI Lint style)
2026-08-29
gitlab.com
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Unlimited public and private Git repos with up to 5 collaborators. Includes CI/CD, Static Hosting, Container Registry, Project Management and Issue Tracking
2026-08-29
appcircle.io
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An enterprise-grade mobile DevOps platform that automates the build, test, and publish store of mobile apps for faster, efficient release cycle. Free for 30 minutes max build time per build, 20 monthly builds and 1 concurrent build.
2026-08-29
Apply.build
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Build and deploy your GitHub app for free with 0.5 vCPUs / 512 MiB RAM, European servers, automatic firewall, real-time performance metrics. Run Node.js, Python, Go, Java, static sites, microservices, and more.
2026-08-29
Argos
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Open Source visual testing for developers. Unlimitedprojects, with 5,000 screenshots per month. Free for open-source projects.
2026-08-29
CodeCommit
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5 active users, 5k repositories/account, 50GB storage/month and 10K requests/month
2026-08-29
Azure Pipelines
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10 free parallel jobs with unlimited minutes for open source for Linux, macOS, and Windows
2026-08-29
beanstalkapp.com
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A complete workflow to write, review, and deploy code), a free account for one user, and one repository with 100 MB of storage
2026-08-29
Bencher
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A continuous benchmarking tool suite to catch CI performance regressions. Free for all public projects.
2026-08-29
Bitbucket
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Unlimited public and private Git repos for up to 5 users with Pipelines for CI/CD
2026-08-29
buddy.works
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A CI/CD with five free projects and one concurrent run (120 executions/month)