Show HN: Rigour – Open-source quality gates for AI coding agents https://ift.tt/4cEdAwt

Show HN: Rigour – Open-source quality gates for AI coding agents Hey HN, I built Rigour, an open-source CLI that catches quality issues AI coding agents introduce. It runs as a quality gate in your workflow — after the agent writes code, before it ships. v4 adds --deep analysis: AST extracts deterministic facts (line counts, nesting depth, method signatures), an LLM interprets what the patterns mean (god classes, SRP violations, DRY issues), then AST verifies the LLM didn't hallucinate. I ran it on PicoClaw (open-source AI coding agent, ~50 Go files): - 202 total findings - 88 from deep analysis (SOLID violations, god functions, design smells) - 88/88 AST-verified (zero hallucinations) - Average confidence: 0.89 - 120 seconds for full codebase scan Sample finding: pkg/agent/loop.go — 1,147 lines, 23 functions. Deep analysis identified 5 distinct responsibilities (agent init, execution, tool processing, message handling, state management) and suggested specific file decomposition. Every finding includes actionable refactoring suggestions, not just "fix this." The tool is local-first — your code never leaves your machine unless you explicitly opt in with your own API key (--deep -k flag). Tech: Node.js CLI, AST parsing per language, structured LLM prompts with JSON schema enforcement, AST cross-verification of every LLM claim. GitHub: https://ift.tt/CiDYj9n Would love feedback, especially from anyone dealing with AI-generated code quality in production. https://rigour.run February 21, 2026 at 10:45PM

Show HN: Manifestinx-verify – offline verifier for evidence bundles (drift) https://ift.tt/9CaKeEi

Show HN: Manifestinx-verify – offline verifier for evidence bundles (drift) Manifest-InX EBS is a spec + offline verifier + proof kit for tamper-evident evidence bundles. Non-negotiable alignment: - Live provider calls are nondeterministic. - Determinism begins at CAPTURE (pinned artifacts). - Replay is deterministic offline. - Drift/tamper is deterministically rejected. Try it in typically ~10 minutes (no signup): 1) Run the verifier against the included golden bundle → PASS 2) Tamper an artifact without updating hashes → deterministic drift/tamper rejection Repo: https://ift.tt/VD8WbK9 Skeptic check: docs/ebs/PROOF_KIT/10_MINUTE_SKEPTIC_CHECK.md Exit codes: 0=OK, 2=DRIFT/TAMPER, 1=INVALID/ERROR Boundaries: - This repo ships verifier/spec/proof kit only. The Evidence Gateway (capture/emission runtime) is intentionally not included. - This is not a “model correctness / no hallucinations” claim—this is evidence integrity + deterministic replay/verification from pinned artifacts. Looking for feedback: - Does the exit-code model map cleanly to CI gate usage? - Any spec/report format rough edges that block adoption? https://ift.tt/VD8WbK9 February 20, 2026 at 11:57PM

Show HN: HelixDB Explorer – A macOS GUI for HelixDB https://ift.tt/eROQtKD

Show HN: HelixDB Explorer – A macOS GUI for HelixDB https://ift.tt/RvDpw37 February 20, 2026 at 11:18PM

Show HN: A small, simple music theory library in C99 https://ift.tt/u8rhQ9O

Show HN: A small, simple music theory library in C99 https://ift.tt/muQ4UaY February 20, 2026 at 04:24AM

Show HN: Hi.new – DMs for agents (open-source) https://ift.tt/4VaYAI7

Show HN: Hi.new – DMs for agents (open-source) https://www.hi.new/ February 20, 2026 at 02:50AM

Show HN: Astroworld – A universal N-body gravity engine in Python https://ift.tt/qgVhtmJ

Show HN: Astroworld – A universal N-body gravity engine in Python I’ve been working on a modular N-body simulator in Python called Astroworld. It started as a Solar System visualizer, but I recently refactored it into a general-purpose engine that decouples physical laws from planetary data.Technical Highlights:Symplectic Integration: Uses a Velocity Verlet integrator to maintain long-term energy conservation ($\Delta E/E \approx 10^{-8}$ in stable systems).Agnostic Architecture: It can ingest any system via orbital elements (Keplerian) or state vectors. I've used it to validate the stability of ultra-compact systems like TRAPPIST-1 and long-period perturbations like the Planet 9 hypothesis.Validation: Includes 90+ physical tests, including Mercury’s relativistic precession using Schwarzschild metric corrections.The Planet 9 Experiment:I ran a 10k-year simulation to track the differential signal in the argument of perihelion ($\omega$) for TNOs like Sedna. The result ($\approx 0.002^{\circ}$) was a great sanity check for the engine’s precision, as this effect is secular and requires millions of years to fully manifest.The Stack:NumPy for vectorization, Matplotlib for 2D analysis, and Plotly for interactive 3D trajectories.I'm currently working on a real-time 3D rendering layer. I’d love to get feedback on the integrator’s stability for high-eccentricity orbits or suggestions on implementing more complex gravitational potentials. https://ift.tt/dYj9M2N February 20, 2026 at 01:27AM

Show HN: Nonograms – Friends-only puzzle room with replays and leaderboards https://ift.tt/aDMguKi

Show HN: Nonograms – Friends-only puzzle room with replays and leaderboards Invite code: hackernews. No email required for signup. My friend group loves playing nonograms and competing against each other, but we always send each other screenshots of the solved game grid and time after the fact. So from the start, I knew I wanted leaderboards, replays, and shareable links. I also added PWA support so it can be added to the home screen on mobile and an offline play mode. No ads, analytics or nonsense, just nonograms. Some other goodies as well such as YouTube-like scrubber and KDE-based visualization in replays. https://ift.tt/BrTEMUX Tech stack: React + TypeScript on Vite, hosted on Cloudflare Pages with D1 and Workers https://ift.tt/eDv6IPz February 18, 2026 at 11:23PM