Show HN: Tag Promptless on any GitHub PR/Issue to get updated user-facing docs https://ift.tt/PZqth8w

Show HN: Tag Promptless on any GitHub PR/Issue to get updated user-facing docs Hi HN! I'm Prithvi—my co-founder Frances and I launched Promptless almost a year ago here ( https://ift.tt/6bagnOV ). It's an AI teammate that watches your workflows—code changes, support tickets, Slack threads, etc.—and automatically drafts doc updates when it spots something that should be documented. Frances and I really appreciated the feedback from our first launch. Today we’re launching Promptless 1.0, which addresses our biggest learnings from the last 12 months. I also made it way easier to try it out. You can tag @promptless on any open-source Github PR or Issue with a doc update request, and Promptless will create a fork and open a PR for your docs to help. Feel free to use our own docs as a playground: https://ift.tt/Q0UAJ49 Or, you can sign up at https://promptless.ai to get free access for your own docs for the next 30 days. Here's a demo video: https://youtu.be/IWwimHCEY7Y For me, the coolest part of the last year has been seeing how users got creative with Promptless. One user has Promptless listening in to all their Slack Connect channels, so whenever they answer a customer question, Promptless figures out if their docs should be updated and drafts an update if so. Another user has Promptless processing every customer meeting transcript and updating their internal docs after each meeting: customer dashboards, feature request pages, etc. Some of the biggest things that are new with version 1.0: - Automatically updating screenshots: this was by far our most requested feature. The need here was always clear. People would exclude screenshots from docs because they’d get stale quickly, even though they knew screenshots would be helpful to users . A year ago, we just couldn't ship a good enough solution, but given how much LLMs' visual grounding has improved in the last year, now we've got something we're proud of. - Slop-free writing: The most common critique on early Promptless suggestions was that even though they were accurate, they could sound generic or verbose, or might just reek of AI slop. Promptless 1.0 is 3.5x better at this (measured by voice-alignment compared to what users actually published), through a combination of fine-tuned models, sub-agents, and alignment on user-defined preferences. - Open-source program: We're especially proud of this—Promptless is now free for CNCF/Linux Foundation projects (reach out if you’re a maintainer!). You can take a look at how Promptless is supporting Vitess (a CNCF-graduated project) with their docs here: https://ift.tt/W5udsp0 Check it out and let us know if you have any questions, feedback, or criticism! February 24, 2026 at 11:31PM

Show HN: Unlock the best engineering knowledge in papers for your coding agent https://ift.tt/rtJancK

Show HN: Unlock the best engineering knowledge in papers for your coding agent https://ift.tt/n6iFlu0 February 23, 2026 at 11:03PM

Show HN: AgentDbg - local-first debugger for AI agents (timeline, loops, etc.) https://ift.tt/AmSlWYw

Show HN: AgentDbg - local-first debugger for AI agents (timeline, loops, etc.) AgentDbg is a local-first debugger for AI agents. It records structured runs (LLM calls, tool calls, state, errors) to JSONL and shows the timeline UI locally. There is no need for cloud, accounts, and no telemetry. Flow is as simple as: 1. Run an agent 2. `agentdbg view` 3. Inspect the timeline, loop warnings, errors, etc. v0.1 includes `@trace` and `traced_run`, recorders, loop detection, best-effort redaction (by default), local UI, export. I also started working on integrations: there is an optional LangChain/LangGraph callback. * Repo: https://ift.tt/yhHd5cL * Demo: `python examples/demo/pure_python` and then `agentdbg view` Would love feedback on: 1. Trace format 2. Integrations to prioritize in the next several days 3. What you would want for deterministic replay https://ift.tt/yhHd5cL February 23, 2026 at 11:14PM

Show HN: Saga – SQLite project tracker for AI coding agents https://ift.tt/OuTxX79

Show HN: Saga – SQLite project tracker for AI coding agents https://ift.tt/Sdt9acg February 23, 2026 at 12:19AM

Show HN: Rendering 18,000 videos in real-time with Python https://ift.tt/WuCNpfh

Show HN: Rendering 18,000 videos in real-time with Python https://ift.tt/mGPjidF February 22, 2026 at 09:16PM

Show HN: Winslop – De-Slop Windows https://ift.tt/snKENo5

Show HN: Winslop – De-Slop Windows https://ift.tt/rcJZypb February 22, 2026 at 01:26AM

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