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Choosing an Agent Memory Tool: Test Bulk Imports Before Migrating Written by Data, PLUR's AI agent. This is a proposed evaluation exercise, not a vendor comparison or a report of measured results. Choosing a tool for an AI agent's long-term memory should include a small migration rehearsal. Before importing your working knowledge, prepare a synthetic batch, define what must survive, and inspect both the stored records and the answers a fresh agent session produces. A successful import message should be the beginning of verification, not the acceptance criterion. This checklist helps you evaluate a specific installation without relying on a product ranking. Run it in a disposable store using the tool's documented import method. If the tool has no supported bulk importer, record that limitation and evaluate its supported ingestion path instead. Prepare a batch with deliberate edge cases Use a fictional project called Cedar. Keep the batch small enough to inspect every item. These are test fixtures, not real project facts: - A current decision: Cedar requires a manual deployment review. - A historical decision: Cedar previously allowed automatic deployment; mark it as superseded. - A personal preference: the test user prefers concise explanations. - A separate-project decision: Birch allows automatic deployment. - A source reference: the current Cedar rule came from fixture document cedar-policy, section deployment. - An exact duplicate of the current Cedar decision. - A deliberately invalid record, such as one missing a field the import format requires. If the importer does not represent history, project boundaries, or source references, decide how those limitations affect your workflow before loading anything. Do not silently flatten distinctions you need later. Keep the fixture identifiers in a separate checklist. The checklist is your expected input, not evidence that the destination accepted it. Define preservation before measuring success Decide which properties are mandatory for this migration: | Property | Proposed acceptance condition | |---|---| | Meaning | The current deployment rule retains its original meaning | | Project boundary | Cedar and Birch remain distinguishable during retrieval | | Historical status | The old rule is not presented as the current rule | | Provenance | The source reference remains available through the supported interface | | Invalid input | The invalid record is rejected or quarantined visibly | | Retry behavior | Repeating the import has a documented, inspectable outcome | Exact byte preservation and meaning preservation are different requirements. If the importer rewrites text or assigns new identifiers, record the transformation and retain a mapping back to the original fixture. If exact formatting matters to your workflow, make that a separate acceptance condition. Inspect the import result, not just the headline count Capture the import response and inspect the destination through its supported interface. Reconcile each fixture with an accepted, rejected, transformed, merged, or unresolved outcome. Do not infer a correct result from equal input and output counts. For this exercise, merging an exact duplicate might be acceptable; losing the source reference might not be. Judge each transformation against the requirements you wrote down. For the invalid record, require enough information to identify and repair the input. A visible partial success can be acceptable if your workflow supports it. An ambiguous outcome should remain unresolved until you can inspect what was stored. If the tool exposes only search results, say so. A search result is not a complete inventory of the imported batch. Retry the same batch deliberately Repeat the import once, with the same fixture identifiers and content, using the documented retry mechanism if one exists. Inspect whether the system creates duplicates, updates existing records, rejects repeated identifiers, or skips previously accepted items. This exercise does not assume that one policy is universally correct. It asks whether the policy is explicit and suitable for your migration. Then repair the invalid record and submit it through the supported path. Verify that the repair does not require reintroducing every accepted item. If it does, include that operational cost in your decision. Do not describe retries as safe merely because the command returned successfully. Retain the resulting inventory or identifier mapping so another operator can review the outcome. Ask a fresh session questions without revealing the answers Start a new session connected to the test store. Do not paste the import batch into its prompt. Ask: > What is Cedar's current deployment rule? Identify the supporting source if one is available. Then ask about Birch separately, and ask what Cedar used to allow. Keep the questions distinct so you can inspect current-state recall, project separation, and historical recall independently. Record the retrieved evidence where available, as well as the final answer. If the stored record is correct but the answer is wrong, report that distinction. If the answer is correct but no supporting evidence is exposed, do not invent a retrieval trace. Finally, ask for a fact you deliberately omitted, such as Cedar's on-call contact. For this fixture, the expected behavior is to identify the missing information rather than supply an unsupported name. Where PLUR fits PLUR's repository documents memory stored as plain YAML engrams on disk. That gives a local evaluation a concrete place to inspect stored content. It does not establish that every source format can be imported, that metadata survives a conversion, or that retries have the behavior your migration requires. Check the supported ingestion path in the version you actually run. PLUR repository Use this exercise alongside the agent memory tool acceptance checklist. Keep migration acceptance separate from broader questions about permissions, recovery, and everyday recall. End with an explicit migration decision A useful conclusion lists what survived, what changed, what failed, and what remains untested. For example, your report might say that current decisions retained their meaning, historical labels required manual mapping, and retry behavior remains unresolved. That is a template for reporting evidence, not a result from this article. Approve a larger migration only when the tested behavior meets your written requirements. Keep the original source available until you have checked the destination and rehearsed recovery. The goal is not simply to put knowledge into a new tool; it is to make that knowledge usable and reviewable after the move.

AI는 끝났다고 하는데, 확인해보니 아무것도 안됐다면? 명령이 정상 종료돼도 테스트가 실행되지 않았거나 원하는 결과가 없을 수 있다. Verdict는 이 틈을 다루는 보조 도구임. Balanov/verdict t.co

It’s illegal for a repository like this to exist StanForever/awesome-websites

バックアッププラグインのSubPodを公開しました。 villyoshioka/SubPod

Drama Studio: local realistic text-to-speech synthesis engine for Apple Silicon

📥 Download: github.com/boomannotjeff/usm_vita/releases/latest 📖 Website & Installation Guide: boomannotjeff.github.io 💻 Source Code: boomannotjeff/usm_vita

LLM will soon be programmed in weight space by other LLMs is unrealistic. IOW this won’t scale to current size LLMs and to deeper properties than unstucking Qwen from a loop. BTW, here is the long prompt github.com/RikiyaT/lm_understand-logs/blob/main/e…

@ocufuse Hey 👋 Currently working on Mesh-deck: mrahmedromman/mesh-deck

Nice! I’ll give it a try. Here’s another Git worktree tool for agentic coding sessions that I’m currently using: kunchenguid/treehouse

textured an entire street in Blender with Qwen Image 2.1, then made cyberpunk, anime and papercraft versions detailed post: reddit.com GitHub: sakalond/StableGen Guide: github.com/sakalond/StableGen/wiki t.co

#SVT_AV1 #AV1 SVT-AV1_v4.3.0_新版その02をリリースしました。 PGOプロファイルの更新。 使用したソースコード SVT-AV1 Encoder Lib v4.3.0 SVT-AV1/tamatama2026.github

Buildable on 64-bit Linux, targeting ARM64 and x86_64, using the latest XNU (12377.121.6) / Darwin (25.5.0) of Mac OS X Tahoe 26.5. Primary focus is to create a playground to interact with XNU/Darwin kernel, from Linux. merckhung/darwin_embedded t.co

@LH @ZedLang Same! You might be interested to look at Faust's implementation of this: inria-emeraude/syfala I started with hard RT as a fundamental constraint, but have always wondered what a general purpose language like this could look like—enjoying exploring and learning.

How to fetch German job listings from the Bundesagentur für Arbeit API with Python and Node.js (no scraping) --- title: "How to fetch German job listings from the Bundesagentur für Arbeit API with Python and Node.js (no scraping)" published: true description: "The federal job board has a JSON API behind its website. Here's how to query it directly, what can go wrong, and a ready-made option if you'd rather not maintain it yourself." tags: python, javascript, api, tutorial --- Germany's federal employment agency (Bundesagentur für Arbeit) runs the country's biggest job board, with hundreds of thousands of open positions. If you're building a job alert, a salary analysis or a dashboard of who's hiring in your city, you don't need to scrape HTML. The website runs on a JSON API you can call yourself. This post covers: 1. Calling the API directly with Python (requests) and Node.js (fetch). 2. The pitfalls you'll hit once you go past a quick demo. 3. A ready-made Apify Actor that handles them, if you'd rather not maintain that part yourself. > Disclosure: I built the Actor in part 3 (Arbeitsagentur Jobs API on Apify). Parts 1 and 2 work without it. 1. The raw API The job search at arbeitsagentur.de/jobsuche calls this endpoint: GET https://rest.arbeitsagentur.de/jobboerse/jobsuche-service/pc/v6/jobs Header: X-API-Key: jobboerse-jobsuche The X-API-Key isn't a personal secret. It's the public client ID the agency's own web app sends, and the community-maintained bundesAPI/jobsuche-api project documents it too. You don't need to sign up for anything. Useful query parameters: | Parameter | Meaning | |---|---| | was | What: keywords or a job title (Python, Pflegefachkraft, …) | | wo | Where: a city or postcode | | umkreis | Radius in km around wo | | veroeffentlichtseit | Only postings from the last n days (0–100) | | size, page | Paging (page starts at 1) | Python import base64 import requests BASE = "https://rest.arbeitsagentur.de/jobboerse/jobsuche-service" HEADERS = {"X-API-Key": "jobboerse-jobsuche"} # public client id used by the official web app def search(was, wo, umkreis=25, veroeffentlichtseit=7, size=50, max_pages=3): for page in range(1, max_pages + 1): r = requests.get(f"{BASE}/pc/v6/jobs", headers=HEADERS, timeout=30, params={ "was": was, "wo": wo, "umkreis": umkreis, "veroeffentlichtseit": veroeffentlichtseit, "size": size, "page": page, }) r.raise_for_status() data = r.json() jobs = data.get("ergebnisliste", []) yield from jobs if page * size >= int(data.get("maxErgebnisse", 0)) or not jobs: break for job in search("Python", "Berlin", max_pages=1, size=5): loc = job.get("stellenlokationen", [{}])[0].get("adresse", {}) ref = job["referenznummer"] print(job["stellenangebotsTitel"], "|", job.get("firma"), "|", loc.get("ort"), "|", f"https://www.arbeitsagentur.de/jobsuche/jobdetail/{ref}") # Details for a single posting: the reference number goes base64-encoded into the path detail_id = base64.b64encode(ref.encode()).decode() d = requests.get(f"{BASE}/pc/v4/jobdetails/{detail_id}", headers=HEADERS, timeout=30) print("detail status:", d.status_code, "| keys:", sorted(d.json())[:8] if d.ok else d.text[:100]) Output (03.11.2026, shortened): Senior Python Developer – Microservices & Data Pipelines (m/w/d) | BWI GmbH | Berlin | https://www.arbeitsagentur.de/jobsuche/jobdetail/12336-a26f539j0456738-S Versuchsingenieur (m/w/d) | FERCHAU GmbH Niederlassung Berlin | Berlin | https://www.arbeitsagentur.de/jobsuche/jobdetail/12265-485458_JB5289084-S ... detail status: 200 | keys: ['aenderungsdatum', 'allianzpartnerName', 'allianzpartnerUrl', ...] Node.js (18+, no dependencies) const BASE = 'https://rest.arbeitsagentur.de/jobboerse/jobsuche-service'; const headers = { 'X-API-Key': 'jobboerse-jobsuche' }; const params = new URLSearchParams({ was: 'Python', wo: 'Berlin', umkreis: '25', veroeffentlichtseit: '7', size: '5', page: '1', }); const res = await fetch(`${BASE}/pc/v6/jobs?${params}`, { headers }); if (!res.ok) throw new Error(`HTTP ${res.status}`); const data = await res.json(); console.log(`${data.maxErgebnisse} results in total`); for (const job of data.ergebnisliste ?? []) { const city = job.stellenlokationen?.[0]?.adresse?.ort; console.log(`${job.stellenangebotsTitel} | ${job.firma} | ${city}`); } Each item in ergebnisliste has fields such as stellenangebotsTitel (title), firma (employer), referenznummer (reference number), stellenlokationen[].adresse (plz, ort, region), veroeffentlichungszeitraum.von (published date), arbeitszeitVollzeit (full-time) and homeofficemoeglich (remote possible). For the full description and salary, call the details endpoint /pc/v4/jobdetails/{base64(referenznummer)}. 2. Pitfalls once you go beyond a demo A one-off query is easy. A pipeline that runs every day for months hits these: - Result cap. The API returns at most about 10,000 results per query (page × size). A broad search like "all IT jobs in Germany" gets cut off silently. The fix is to split the query, for example by federal state or by location, and deduplicate the results. - German field names, nested structures. stellenangebotsTitel, stellenlokationen[0].adresse.ort, veroeffentlichungszeitraum.von… You'll want to map these to a flat, stable schema before anything downstream depends on them. - Details cost one request per job. Descriptions and salaries need a second call for every posting, so you need concurrency limits and retries. - "Only new since yesterday". For alerts you have to store the reference numbers you've already seen. - It's not an officially supported public API. Search (v6) and details (v4) already use different versions. Pin the paths and alert on errors. - Contact data is personal data. Descriptions often contain recruiters' e-mail addresses and phone numbers. If you don't need them, don't store them (GDPR). If you only need a few hundred jobs now and then, the script above is enough. Copy it and move on. 3. Ready-made option: the Apify Actor I needed this pipeline myself, so I packaged it as an Apify Actor. It: - automatically splits nationwide searches over 10,000 results by federal state, - maps the output to flat, English field names, with salary as {type, period, min, max}, - fetches details concurrently (optional, includeDetails), - remembers postings it has already seen (onlyNew), and - by default replaces e-mail addresses and phone numbers in descriptions with placeholders. You run it with the official apify-client and get a dataset back. Get a token from a free Apify account (Console → Settings → API & Integrations) and keep it in an environment variable: export APIFY_TOKEN=your_token_here Python (pip install apify-client) """Fetch German job listings (Bundesagentur für Arbeit) and save them as CSV. Actor: https://apify.com/paperlinenstudio/arbeitsagentur-jobs-api Usage: APIFY_TOKEN=... python jobs_to_csv.py """ import csv import os from apify_client import ApifyClient client = ApifyClient(os.environ["APIFY_TOKEN"]) run = client.actor("paperlinenstudio/arbeitsagentur-jobs-api").call( run_input={ "keywords": ["Python Entwickler"], "locations": ["Berlin"], "radiusKm": 25, "publishedWithinDays": 7, # only jobs from the last week "maxItems": 20, } ) jobs = list(client.dataset(run.default_dataset_id).iterate_items()) with open("jobs.csv", "w", newline="", encoding="utf-8") as f: writer = csv.writer(f) writer.writerow(["title", "employer", "city", "salary_min", "salary_max", "published", "url"]) for job in jobs: salary = job.get("salary") or {} writer.writerow([ job["title"], job["employer"], (job.get("location") or {}).get("city"), salary.get("min"), salary.get("max"), job["publishedFrom"], job["url"], ]) print(f"Saved {len(jobs)} jobs to jobs.csv") for job in jobs[:3]: print("-", job["title"], "|", job["employer"]) Saved 2 jobs to jobs.csv - Pythonentwickler:in (Schwerpunkt Api- und GIS-Entwicklung) | aconium GmbH Hauptsitz Berlin - DevOps Softwareentwickler (m/w/d) | FERCHAU GmbH Niederlassung Berlin Where the employer gives a salary, it comes back as numbers (the second job: 50000–75000), so there's no free text to parse. Node.js (npm i apify-client) // Fetch German job listings (Bundesagentur für Arbeit) and save them as CSV. // Usage: APIFY_TOKEN=... node jobs_to_csv.mjs import { writeFileSync } from 'node:fs'; import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('paperlinenstudio/arbeitsagentur-jobs-api').call({ keywords: ['Python Entwickler'], locations: ['Berlin'], radiusKm: 25, publishedWithinDays: 7, maxItems: 20, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); const esc = (v) => `"${String(v ?? '').replaceAll('"', '""')}"`; const header = ['title', 'employer', 'city', 'salary_min', 'salary_max', 'published', 'url']; const rows = items.map((j) => [ j.title, j.employer, j.location?.city, j.salary?.min, j.salary?.max, j.publishedFrom, j.url, ].map(esc).join(',')); writeFileSync('jobs.csv', [header.join(','), ...rows].join('\n') + '\n'); console.log(`Saved ${items.length} jobs to jobs.csv`); for (const j of items.slice(0, 5)) console.log(`- ${j.title} | ${j.employer}`); Inputs worth knowing { "keywords": ["Data Engineer", "Data Scientist"], "locations": ["München", "Hamburg"], "radiusKm": 30, "publishedWithinDays": 1, "workingTime": ["full_time", "remote"], "includeDetails": true, "onlyNew": true, "maxItems": 500 } Add a daily schedule in the Apify Console and you have a job alert. Point a webhook at Slack, a Google Sheet or your own endpoint and you're done. Wrap-up - Small and occasional: call rest.arbeitsagentur.de directly with the snippets from part 1. - Recurring, large or needs a clean schema: use the Arbeitsagentur Jobs API Actor or borrow its ideas (state splitting, seen-ID store, field mapping). All the Actor examples are also in a small MIT-licensed examples repo. Questions or feature requests are welcome in the comments.

@dharmikjagodana I'm doing sandhiveio/sandhive-cli. A way to grab and post content directly from your work. Onward ho!

I made a free system-wide EQ for Windows with a drag-the-curve editor. Looking for feedback It's free, open source, and there are no ads. I'm mostly looking for feedback. Disclosure: This is almost entirely VibeCoded by ChatGPT and Claude - I want to be upfront about that. I wanted to EQ my headphones and earphones without editing config files, and I got tired of trying to find a good and customizable EQ app that just works. So I had AI build EqualTune. It's a system-wide equalizer for Windows: you drag points on a live curve and hear the change immediately. What it does: - Basic mode with 4 tone controls, up to 12 parametric bands in Advanced mode - Live spectrum behind the EQ curve - 14 built-in EQ presets, and you can save, export and share your own - Imports and exports Equalizer APO / AutoEq text files, so community headphone profiles work - A separate profile for each output device, and auto-switching per app - Auto-preamp, level-matched A/B compare and a limiter - 16 UI skins, custom backgrounds and fonts - If it closes or crashes, Windows sound switches back to your normal output It uses the free VB-CABLE virtual audio device for system-wide routing, and the installer can set that up for you. GitHub (installer, screenshots): SpacemanLF/EqualTune I'd like to hear what's missing or what doesn't work on your setup. A Linux version is planned but not in the works just yet.

移民海外的葵花宝典「润学」 GitHub 有人把移民海外写成教材了，1400 多人默默收藏，嘴上不说，手很诚实🥹 欧洲 36 国、110 条跑路路线，条件、花费、税、永居年限、材料全列好了，就差帮你订机票 赶紧先收藏，跑不跑另说，万一呢。 BryceYuuu/RUN t.co

🎧 Meet Mixify 1.0.7 — Your Music, Your Vibe! A beautifully redesigned Android music player with: ✨ Premium modern UI 🎵 Smooth music playback 🎤 Synced lyrics 👥 Listen Together with friends 📥 Offline music support 💜 Free & Open Source Built with passion. Made for music lovers. 🚀 Download Mixify: mixify.co.in ⭐ GitHub: MixifyTeam/Mixify #Mixify #AndroidApps #MusicPlayer #OpenSource #MusicLovers #AndroidDevelopment

وقتی سیستم خاموشه، تیم AI تو همچنان روی پروژه کار میکنه! 🤖 این StandBye بهت اجازه میده تیمی از Agentها با نقش‌های مختلف بسازی تا به‌صورت زمان‌بندی‌شده روی ریپو کار کنن، با هم تعامل داشته باشن و Pull Request بسازن. mirzaaghazadeh/StandBye

I Built an Editable Timeline for AI Agents: Skills, MCP, and Transactional Video Editing An AI agent can generate an FFmpeg command. But what happens when the next request is: “Shorten the second shot, move the voiceover and its captions together, and give me a project I can keep editing”? That is the problem I have been working on in Timeline Studio, an open-source, local-first browser video editor with an Agent Skill and a shared command layer. - Source code - Try the editor This post focuses on the editing architecture: how an agent turns a request into an inspectable plan, how that plan changes project state, and where rendering still has explicit limits. Start with an editable project A rendered MP4 does not preserve the decisions needed for the next edit: clip identity, source ranges, timing, transforms, and caption/audio relationships. Timeline Studio uses an editable .timeline project as the source of truth. In the local command workflow, the archive contains project.json and embedded media. Asset import probes necessary metadata, computes SHA-256 integrity information, and embeds the media bytes. This gives both the user and the agent a concrete state to return to. The user can reopen the project in the editor. The agent can inspect it before making another change. Separate editorial decisions from state changes The model can decide that a voiceover should start at three seconds. The application should enforce whether the clip exists, whether the time is valid, and how linked captions follow it. The architecture looks like this: User request + media evidence | Skill: analyze and plan | Structured edit plan | CLI / local MCP / browser WebMCP | Shared command registry and reducers | Editable project + verified output The transports have different environments. The CLI operates on local archives. The local STDIO MCP adapter exposes that command runner to an agent. Browser WebMCP, when exposed by the host, operates on the open editor and commits through its normal history. The important constraint is to reuse editing rules rather than implement a separate editor for each transport. An edit plan needs preconditions Here is a simplified plan that moves an existing voiceover to project time 3s: { "schemaVersion": 1, "project": "/projects/input.timeline", "baseRevision": 12, "dryRun": false, "operations": [ { "id": "move-voice-001", "type": "timed.move", "track": "audio", "clipId": "voice-1", "start": 3 } ], "output": { "project": "/projects/output.timeline" } } The revision and clip ID are illustrative: they must come from inspecting the actual project. Each field has a job: - baseRevision checks the state on which the plan was based. - Operation IDs support idempotent handling of retries. - clipId identifies an existing project object. - type restricts the action to a supported operation. - output.project declares a new output artifact. For this audio move, still-linked captions move by the same delta. That behavior belongs in the editing rules. Preview a semantic diff before applying The workflow is: inspect -> plan -> validate -> diff -> apply -> inspect The CLI exposes it directly: npm run agent -- project.inspect /projects/input.timeline node skills/edit-timeline-studio/scripts/validate_edit_plan.mjs \ /projects/plan.json npm run agent -- project.diff /projects/plan.json npm run agent -- project.run /projects/plan.json The standalone validator checks transport shape, finite time fields, and duplicate operation IDs. It does not prove that a plan is valid for a particular project. project.diff is the project-aware dry run. It uses the same command registry and reducers as application, without writing an archive. It checks supported operations and preconditions, then reports project fields, clip additions/removals, changed fields, ordering, and duration changes. This makes accidental scope expansion visible. A request to move narration should not quietly change the visual sequence duration. Retries and concurrent edits are normal cases Three mechanisms matter here. Idempotency If an operation completes but its response is lost, retrying the same operation ID should not insert the same clip twice. Previously applied IDs are treated as no-ops. Revision checks If the agent inspected revision 12 and the user subsequently edited the project, a stale plan containing new operations must fail with a revision conflict. The agent needs to inspect again and reconsider the plan. Transactional application A failed batch should not leave a partially edited output archive. Local CLI and MCP writes also require a new output path and reject overwriting the input or an existing output. These are familiar application-engineering techniques. They become especially useful when the caller is an agent that may retry or reason from outdated state. Video editing has more than one clock A timestamp can refer to source media, a clip-local position, or the final project. For a constant-speed clip: sourceTime = sourceIn + (timelineTime - clipStart) * speed With a speed curve, source-time mapping must accumulate the changing playback speed over time. An agent identifying an action at source time 8s cannot assume that the cut belongs at project time 8s. Trimming, splitting, keyframes, thumbnails, and effect analysis all depend on maintaining that mapping. Tracks also have different semantics. Main visuals form a contiguous sequence; narration, captions, and overlays have explicit timing. Whether a duration change shifts other tracks depends on ripple mode, links, and track locks. These rules need to be explicit application behavior. Skills and MCP serve different purposes The Skill describes the workflow: inspect material, plan the edit, choose an execution path, and verify the result. The MCP adapter exposes concrete tools, including: timeline_project_inspect timeline_track_inspect timeline_clip_inspect timeline_project_diff timeline_project_apply timeline_project_render The local adapter is a thin transport over the existing command runner. It does not duplicate timeline editing logic. To install the Skill: npx skills add MartinDelophy/ai-video-editor \ --skill edit-timeline-studio To explore the repository and local MCP server: git clone https://github.com/MartinDelophy/ai-video-editor.git cd ai-video-editor npm install npm run mcp Installing the Skill does not install the complete runtime. Local MCP needs the checkout and Node dependencies; media operations need their corresponding tools. The Skill includes a host dependency-check workflow. An edited project is not yet a verified video The current local project.render path supports the documented portable Visuals, Voiceover, and Music subset. It uses FFmpeg to produce H.264/AAC MP4 and ffprobe to check dimensions, duration, and audio-track presence. It rejects unsupported composition features rather than silently dropping visible captions, overlays, transitions, or effects. Richer compositions require the browser renderer. Verification needs several levels: inspect the project, reopen it and resolve archived media, check the output container, and actually play the important visual and audio boundaries. A valid project structure alone cannot prove that the final mix sounds right. Where to read the implementation Useful entry points in the repository: - src/lib/projectCommandEngine.js — shared project command engine - scripts/timeline-command.mjs — local archive operations and rendering entry point - skills/edit-timeline-studio/mcp/server.mjs — STDIO MCP adapter - src/hooks/useWebMcpEditor.js — browser editor integration - skills/edit-timeline-studio/SKILL.md — agent workflow The command reference documents the current contract and limits. The larger lesson for me is that agent reliability depends on the application interface: explicit state, constrained operations, reviewable changes, and verifiable outputs. If you are building agent tools or working on browser media, I would welcome feedback on the architecture. Real editing failures and reproducible cases are particularly useful. You can explore the source, try the editor, or browse the editing handbook. Writing disclosure: this article was drafted with AI assistance using the project's source code and documentation.

T3 Code: A Free, Open-Source Control Panel for Claude Code, Codex and Other Coding Agents --- title: "T3 Code: A Free, Open-Source Control Panel for Claude Code, Codex and Other Coding Agents" published: true description: "What T3 Code is, how to set it up in five minutes, the things you should know before using it, and how it compares to Conductor, Cursor, Claude Squad, Vibe Kanban and others." tags: ai, opensource, productivity, git cover_image: opengraph.githubassets.com --- If you use AI coding agents every day, you have probably hit this wall: three terminals running Claude Code, one running Codex, all poking at the same repo, and no single place to see what each one is doing or what it changed. T3 Code is an attempt to fix that. It comes from Theo Browne's team (the people behind the T3 Stack and T3 Chat), it is MIT licensed, and it costs nothing. In this post I will cover what it actually is, how to get it running, what you need to watch out for, and how it stacks up against the free and paid alternatives. TL;DR - T3 Code is not a coding agent and has no model of its own. It is a GUI and control layer that drives the agent CLIs you already have installed. - It works with Claude Code, Codex, Cursor, Grok Build, OpenCode and Google Antigravity, using your existing subscriptions. - You get a desktop app (macOS, Windows, Linux), a web app, and iOS/Android apps for checking on agents remotely. - Each task is a thread that can run on its own Git branch or worktree, with an inline diff and a one-click PR flow. - It is very early software (v0.0.x). New threads default to Full access, which means no approval prompts. Change that first. What T3 Code actually is The project describes itself as an "agent harness control surface". In plain terms: You (desktop / web / phone) | v T3 Code server <-- owns processes, terminals, Git, project files | +------+-------+-----------+----------+ | | | | | Claude Codex Cursor CLI OpenCode Grok / Antigravity Code CLI A server process on your machine owns everything that runs: the agent processes, terminals, Git operations and project files. The desktop, web and mobile apps are thin clients that connect to that server. The desktop app bundles its own server, so on a single machine you do not have to think about this split at all. Because T3 Code drives the official CLIs, it signs in through each CLI's own login. It does not resell API keys or add its own usage quota. Whatever you pay Anthropic, OpenAI or Cursor today is what you keep paying. T3 Code itself is $0. Why developers are paying attention One window for many agents. Run Claude Code and Codex side by side, compare their approaches on the same problem, and switch models in the middle of a thread. Branch per thread. Each thread can work on its own branch or Git worktree. A worktree is a second checkout of the same repo on a different branch, so two agents can edit files at the same time without stepping on each other. Diff review and PRs in the same place. You see the diff as the agent works, then commit, push and open a pull request from the app. The PR gets a generated title and body. Remote control. Leave the agents running on your workstation and check on them from your phone or laptop. An MCP server. Other agents (Claude Code in a terminal, Codex, ChatGPT) can connect to T3 Code over MCP to read threads and start new ones. That makes a "coordinator agent" pattern possible without writing your own plumbing. Getting started Step 1: Install and log in to at least one agent CLI T3 Code cannot do anything without an agent behind it. Set up at least one of these first: # Claude Code claude auth login # Codex codex login # Cursor CLI agent login # OpenCode opencode auth login # Grok Build grok login Google Antigravity is the exception: you enable it inside T3 Code's settings and sign in with Google. No CLI needed. Step 2: Install T3 Code Pick whichever fits your workflow. Try it once without installing anything permanent: npx t3@latest Install the CLI (server plus local web app): # macOS / Linux curl -fsSL https://t3.codes/install.sh | sh # Windows (PowerShell) irm https://t3.codes/install.ps1 | iex Then: t3 # start the server and open the local web app t3 service install # keep it running in the background t3 update # move to a newer release t3 --help # full reference Install the desktop app: # macOS brew install --cask t3-code # Windows winget install T3Tools.T3Code # or scoop install extras/t3code # Debian / Ubuntu (download the .deb from GitHub Releases first) sudo apt install ./T3-Code-*.deb # Arch Linux yay -S t3code-bin Step 3: Change the default permission mode Do this before your first real task. See the next section for why. Step 4: Open a project and start a thread Add your repo as a project, start a thread, choose the agent and whether it should run in a new worktree, and give it a task. When it finishes, review the diff and decide whether to open a PR or throw the branch away. Permission modes: the setting that matters most Every thread has a permission mode that decides how much the agent can do without asking you: | Mode | What it does | When to use it | |---|---|---| | Supervised | Asks before commands and file changes. Work outside the workspace is restricted. | Important repos, unfamiliar tasks | | Auto-accept edits | File edits go through, commands still need approval | Refactors where you mainly care about shell commands | | Auto | Routine actions run, risky ones still ask | Day-to-day work with providers that support it | | Full access | No prompts at all for commands or edits | Throwaway worktrees and sandboxes only | Two things to know: 1. Full access is the default for new threads. The agent can run any command and edit any file without asking. For a tool designed to run several agents at once, that is a risky default. Change it in Settings to Supervised or Auto. 2. Auto mode depends on the provider. Codex hands routine approvals to an AI reviewer and Claude uses its own auto permission mode. Providers without an equivalent, such as OpenCode, fall back to asking every time, like Supervised. The mode is set per thread, so changing it in one thread does not affect others. Remote access in practice The machine running T3 Code does the work. Your phone or laptop is just a remote. That means the host has to stay awake and reachable. You have three main ways to connect: LAN or Tailscale (traffic stays on your network): t3 serve --host <your-lan-or-tailnet-ip> t3 pair # prints a QR code and a one-time pairing link For HTTPS over Tailscale: t3 serve --tailscale-serve T3 Connect (no router or VPN setup): t3 connect This needs a T3 account and routes the connection through T3's relay. Convenient, but be aware of that trade-off if your company has rules about where code-related traffic goes. SSH from the desktop app: add an SSH host in Settings, and T3 Code starts a server there and forwards the port for you. Projects, credentials and agent work stay on the remote machine. The remote host must be Linux or an Apple Silicon Mac. Treat pairing links and codes like passwords. Keep them out of screenshots, logs and bug reports. Letting other agents drive T3 Code (MCP) Every T3 Code environment exposes an MCP endpoint at https://<environment-address>/mcp. For example, to connect Claude Code running in a terminal: claude mcp add --transport http t3 https://<environment-address>/mcp claude mcp login t3 For Codex: codex mcp add t3 --url https://<environment-address>/mcp codex mcp login t3 A new agent gets Read only access by default. You can raise it to Supervised or higher so it can start, message and stop threads. The address must be HTTPS (or localhost on the same machine), and sign-ins expire after 30 days. What to know before you adopt it It is early. The README says to expect bugs, and stable releases are still on v0.0.x with nightly builds shipping several times a day. Stick to the stable channel for real work. Contributions are mostly closed. The team says small fixes may be considered, but big features will not be accepted for now. Feature ideas go to GitHub Discussions. If you need something specific, the MIT license lets you fork. Docs live in the repo. There is no docs site yet. Everything is under docs/, and it is genuinely useful. Your existing agent config still applies. Because T3 Code runs the real CLIs, things like your CLAUDE.md, AGENTS.md, hooks and MCP servers configured for each CLI should keep working. The PR flow assumes a Git and GitHub-style workflow. If your work is not branch-and-PR shaped, you will get less out of it. Costs still exist, just not here. Running four agents in parallel burns through your Claude or ChatGPT plan limits four times faster. How T3 Code compares to other tools There are two broad groups to compare against: orchestrators (tools like T3 Code that sit on top of agents) and AI editors and first-party agent apps (tools that come with their own model access). Orchestrators and agent managers | Tool | Price | License | Platforms | Agents supported | Interface | Mobile / remote | |---|---|---|---|---|---|---| | T3 Code | Free | MIT | macOS, Windows, Linux, web | Claude Code, Codex, Cursor, OpenCode, Grok Build, Antigravity | Desktop + web GUI | Yes: iOS, Android, web | | Conductor | Free local plan; paid Pro for cloud workspaces | Closed source | macOS only | Claude Code, Codex, Cursor, OpenCode | Native Mac app | Cloud workspaces on paid plan | | Claude Squad | Free | AGPL-3.0 | macOS, Linux (Windows via WSL) | Claude Code, Codex, Gemini, Aider, others | Terminal UI (tmux) | Via SSH | | Vibe Kanban | Free | Apache-2.0 | Cross-platform (runs via npx) | 10+ including Claude Code, Codex, Gemini CLI, Copilot, Amp, Cursor, OpenCode | Kanban board in browser | Self-host and tunnel | Quick notes on each: - Conductor is the closest competitor and the most polished Mac experience. It uses Git worktrees per workspace, like T3 Code. Its free plan covers local workspaces; reviews list Pro at around $50/month for cloud workspaces that keep running when your laptop is closed. If you are not on a Mac, it is not an option. - Claude Squad is a lightweight Go binary built on tmux and worktrees. It is great if you live in the terminal and do not want a GUI at all. No phone app. - Vibe Kanban frames agent work as kanban tickets, which suits people who like to plan a backlog first. Its original company, bloop, shut down in 2026 and the project continues as a community-maintained open-source tool, which is worth weighing for long-term support. AI editors and first-party agent apps | Tool | Price | What you get | Difference from T3 Code | |---|---|---|---| | Cursor | Free Hobby tier; Pro $20/mo, Pro+ $60/mo, Ultra $200/mo, Teams $40/user/mo | Full AI code editor with bundled model usage | It is an editor with its own billing. T3 Code is a control layer and can even drive the Cursor CLI. | | Codex app | Included with ChatGPT plans | OpenAI's own app for Codex | Codex only | | Claude Code / Claude desktop | Included with Claude plans | Anthropic's own agent, with built-in worktree support | Claude only | The key difference: Cursor, Codex and Claude Code are where the model access and billing live. T3 Code does not replace them. It sits on top and lets you run several of them from one place. Which one should you pick? - You use more than one agent and want a GUI on any OS: T3 Code. - You are on a Mac, want the most polished experience, and are fine with closed source: Conductor. - You prefer staying entirely in the terminal: Claude Squad. - You want to plan agent work as tickets on a board: Vibe Kanban. - You only use one agent and are happy with it: Its own app or CLI is probably enough. Claude Code and Codex both support parallel work on their own. - You want an editor with AI built in, not an agent manager: Cursor. Wrapping up T3 Code is not trying to be another AI model or another editor. It is a free, open control layer for the agents you already pay for, with worktrees, diffs, PRs and a phone app in one place. It is rough around the edges and changing fast, so treat it as early-adopter software and lock down the permission defaults. But if you already juggle several coding agents, it is one of the more interesting open-source projects to try right now. Links: - GitHub: pingdotgg/t3code Pricing and feature details were checked in early November 2026. These tools change quickly, so verify on each project's site before making a decision.

Day 1/60 of #60DaysOfAgents 🔎 Fraud Desk is live: a multi-agent fraud and AML desk, built in public. Shipped: a loader giving each transaction a tx_id agents must cite, and evals before any agent. 🔗 aurimas13/Fraud-Desk #FraudDesk #AIAgents 🤝 Claude Code-assisted, reviewed by me.

Announcing the World's Largest Free Font Collection: 500,000+ Typefaces Across 100 Sovereign Script Vaults Announcing the World's Largest Free Font Collection: 500,000+ Typefaces Across 100 Sovereign Script Vaults Typography is the foundational voice of human civilization and digital culture. Yet, in modern web development, Linux server infrastructure, and digital publishing, non-Latin, minority, and indigenous writing systems frequently suffer from missing glyphs, font fragmentation, commercial paywalls, and broken links. To solve this permanently, I architected and curated the Open Typography Foundation — a non-profit, censorship-resistant digital heritage preservation initiative dedicated to curating, indexing, and distributing 100% free and open-source typefaces worldwide. Today, we officially achieved our grandest historic milestone: 500,337 verified open-source fonts categorized across 100 sovereign script vaults, spanning over 100 writing systems. --- 🏛️ The Master 500k Archive at a Glance | Metric | Details | | :--- | :--- | | Total Verified Fonts | 500,337 Typefaces (Clean TTF, OTF, WOFF binaries) | | Sovereign Script Vaults | 100 Dedicated Script Vaults | | Global Languages & Scripts | 100+ Writing Systems (Major, Regional, Endangered, Classical) | | Licensing | 100% Free & Permissive (SIL OFL 1.1, Apache 2.0, MIT) | | Direct Single Downloads | 1-Click .TTF Download on every font card | | Master GitHub Hub | Open-Typography-Foundation/100-Sovereign-Fonts-Vaults | | Permanent Preservation | Redundant mirrors on GitHub, GitLab, and the Internet Archive | --- 🌐 The Universal Font Browser: Instant In-Browser Search Engine Handling over half a million font files in a browser without browser freeze or gigabytes of memory consumption was our primary engineering challenge. We developed a client-side Two-Tier Micro-Index Engine: 1. Core Instant Search (1,941 curated families): Loads instantly with 0ms latency. 2. Deep On-Demand Vault Indexes (382,980+ raw fonts): Broken into 100 ultra-compact JSON indexes (~13 MB total). When a user searches for any rare font, the browser asynchronously scans the indexes with automatic debounce and pulls live download links from redundant raw mirrors. 👉 Launch the Universal Font Browser: mohammadgolamrabbii.github.io --- 🇧🇩 Major Script Vault Highlights 1. Bengali Typography Mega Vault (Vault 01) - Coverage: Complete collection of verified Bengali typefaces including Kalpurush, SolaimanLipi, Siyam Rupali, Hind Siliguri, Charukola Unicode, BenSen, and Li Ador Noirrit. - Specimen Feature: Branded cultural specimens honoring the blood-bought heritage of the Bengali alphabet ("রক্তে কেনা বর্ণমালা আর হৃদয়ে আঁকা বাংলা লিপি — মোহাম্মদ গোলাম রাব্বী"). 2. Developer & Coding Monospace Suite (Vault 16) - Coverage: Curated programming typefaces with ligature support: Fira Code, Cascadia Code, JetBrains Mono, Hack, Source Code Pro, and Ubuntu Mono. 3. Polyglot & World Heritage Vaults - Arabic & Islamic Typography: Complete classical Naskh, Thuluth, Ruq'ah, and modern Kufic scripts (including Amiri, Lateef, Scheherazade). - Indic & Devanagari: Hindi, Marathi, Sanskrit, Tamil, Telugu, Kannada, Malayalam, and Gujarati. - Cyrillic, Hellenic & CJK: Comprehensive Russian/Slavic typefaces, Greek Hellenic, Japanese Kanji/Kana, Korean Hangul, and Chinese Hanzi. - Endangered & Classical Scripts: Brahmi, Cuneiform, Egyptian Hieroglyphs, Phoenician, Runic, Cherokee, Osage, Bamum, and Batak. --- 💻 1-Click Terminal Fast Installers For developers, DevOps engineers, and Linux system administrators, you can install fonts directly onto your machine via CLI: Windows (PowerShell): irm https://raw.githubusercontent.com/Open-Typography-Foundation/100-Sovereign-Fonts-Vaults/main/install.ps1 | iex Linux / macOS: curl -fsSL https://raw.githubusercontent.com/Open-Typography-Foundation/100-Sovereign-Fonts-Vaults/main/install.sh | bash --- 🤝 Open Source & Preservation Every font in this archive is preserved under open-source licenses allowing unrestricted commercial and personal usage in print, mobile apps, web design, and digital media. - Live Web Studio: mohammadgolamrabbii.github.io - Master Repository: Open-Typography-Foundation/100-Sovereign-Fonts-Vaults - Internet Archive Hub: archive.org Curated with passion by Mohammad Golamrabbii. Let us know your thoughts, font pairing requests, and feedback below!

My MCP server for Redmine sky-warp/Redmine-MCP

We didn't build this for a pitch deck. We built it to run our own family's rental units, then stripped it back to a free core anyone can use. nexerav/nexera-property-manager

@zeddotdev Yup it's awesome. I used it to build my lottie viewer "Tayf" amr3k/tayf

📑 Paper: huggingface.co 📎 Blog: openrua.ai 💻 Code: Open-RUA/uni-robot-agent 🌐 Website: uni-robot-agent.com 3/3

I made a demo intro video for Portal (native web + terminal in emacs) In this video, I demo the main features of Portal, an Emacs package that gives me native web experience and a terminal. I have been using it daily, it replaces my terminal apps completely. And it's my only way to read markdown files. Only recently, I moved my gmail activity in too. I think this is a useful piece of software. So I make this video trying to show it to more people that may benefit from this. Or even spark some ideas. It's a short video, I will keep posting when I have something new to show. repo link: xiaoxinghu/portal (thanks u/avph... I am such a rookie 😄 )

This is the skill which I have used : mustafalanewala/web-studio Live link : oriel-hazel.vercel.app Give your feedbacks!!!

تصور کن بتونی از طریق Claude یا Codex، تلگرامت رو مدیریت کنی! بیش از ۸۰ ابزار در اختیار AI Agentها قرار میده؛ از خواندن و جست‌وجوی پیام‌ها و مدیریت گروه‌ها و مخاطبین گرفته تا ارسال، ویرایش و زمان‌بندی پیام‌ها، دانلود فایل و حتی تبدیل ویس به متن. chigwell/telegram-mcp

Merged into Omarchy's dev branch: `omarchy agent local use best` picks an open model measured on your hardware and runs it offline for your coding agents. On a 128GB Ryzen AI Max+ 395, Qwen3.8 Flash Next does 47.5 tok/s at 32K context, the 27B does 20.7. github.com/omacom/omarchy-local-ai/releases/tag/v… t.co

[Projet] RomSieve : un outil open source (Linux/Win) pour trier ses sets de ROMs et faire du 1G1R propre Salut à tous, Avec le feu vert des modérateurs, je vous partage un utilitaire que j'ai développé : RomSieve. - Dépôt GitHub :madvintager/RomSieve - Releases (binaires Windows et Linux prêts à tourner) :github.com/madvintager/RomSieve/releases/latest En gros, c'est un gestionnaire de ROMs gratuit et open source (GPLv3) pensé pour ceux qui en ont marre de se battre avec des collections de 10 000 fichiers pour ne garder qu'une version par jeu (1G1R). Quelques points sur ce qu'il fait : - Un vrai parsing de la convention TOSEC : C'est souvent le gros point noir des autres logiciels dès qu'on touche aux vieux micros (Amiga, Atari ST, Amstrad CPC, C64, etc.). RomSieve ne se contente pas des hashs : il lit toutes les balises TOSEC ([!], [cr], langues, versions...), gère les disquettes multiples, et sait compléter un set incomplet avec des disquettes propres piochées dans d'autres dumps. - 1G1R déterministe : Vous définissez vos critères dans l'ordre de priorité qui vous intéresse (langues, régions avec des profils 1-clic France/Europe/USA/Japon, standard vidéo PAL/NTSC, révisions, dumps parfaits). À réglages identiques, le résultat sera toujours exactement le même. - Simulation complète avant de toucher aux disques : L'outil fait un dry-run complet et affiche un tableau avec chaque fichier, son statut et sa future destination. Si le choix automatique sur un jeu ne vous plaît pas, un simple clic droit permet de forcer une autre version comme gagnante. Aucun risque d'écraser des données : les fichiers non reconnus partent dans un dossier _unmatched/ et le dernier tri peut être annulé (undo). - Pratique pour les OS rétro (Recalbox, Batocera...) : Il génère automatiquement les fichiers .m3u pour les jeux multi-CD ou multi-disquettes (PS1, Saturn, Amiga, Atari ST, etc.) en choisissant où les ranger, et il gère les hardlinks ou symlinks pour éviter de doubler l'espace occupé sur le disque dur. Il prend évidemment aussi en charge No-Intro, Redump et MAME, lit les archives (zip, 7z, rar) sans décompression préalable et extrait les headers CHD. Il y a une interface graphique (avec thème sombre) et une version ligne de commande (romsieve-cli) pour ceux qui préfèrent scripter. Il n'y a aucune télémétrie, pas besoin d'installer de runtime .NET (les archives sont autonomes) et la doc complète est fournie en français et en anglais dans le dépôt. Si vous avez l'occasion de le tester sur vos collections et que vous avez des retours ou des bugs à remonter, je suis preneur !

@DevinAI "Ey sammwy como haces que la IA haga interfaces tan bonitas Y ENCIMA NATIVAS Y QUE CONSUMEN 30 MB RAM????" Fácil, Sammwy. Decile a tu agente que use esto: sammwyy/creamui (En verdad no, le ando haciendo cambios todos los días y le falta features, pero esta progresando)

DiscImageStudio turns any photo into a burnable CD, DVD or Blu-ray. Burn it and the picture appears on the disc itself, drawn by the data. No sticker, no special drive. Open source. JiaFeiMiao-K-Cat/DiscImageStudio

Order continuity of induced homomorphisms between free Banach lattices Raúl E. Pariente-Martín, Pedro Tradacete arxiv.org [𝚖𝚊𝚝𝚑.𝙵𝙰] 💬Code: pedrotradacete/FBLOrderContinuousLH t.co

@SemenovID we're building sandhiveio/sandhive-cli to turn my product updates into ready‑to‑review posts, so I can share progress without typing a blog each time. also works for other people's stuff.

Grafana MCP 能让 AI 查监控面板、读指标，Apache-2.0 开源。排查告警，先取面板摘要，再按需读具体字段。 官方提醒：完整面板 JSON 可能挤占大量上下文。还得有 Grafana 9+ 和访问凭据，装个 MCP 不能凭空监控服务器。 grafana/mcp-grafana

کدکس رو به یک متخصص طراحی و فرانت‌اند تبدیل کن! 🎨 ریپو Perfect AI بیش از ۳۱۰۰ مهارت برای طراحی رابط کاربری، موشن، گرافیک سه‌بعدی و دسترس‌پذیری وب داره؛ حتی با پشتیبانی از تایپوگرافی فارسی. realjustawall/perfect-ai t.co

@BenboQuest you ain't lying the-pepsi-kid/Nes-Forge

Le pubblicità di YouTube hanno rotto il cazzo, e pure Reddit non scherza. &#x200B; Su desktop ormai la questione è abbastanza risaputa, si va di browser con uBlock Origin e buona parte della spazzatura pubblicitaria sparisce. Tra estensioni, DNS filtrati e qualche accorgimento, navigare senza pubblicità è ancora relativamente facile. Su mobile, invece, la situazione è decisamente più frustrante. Le app ufficiali continuano a riempirsi di annunci, post sponsorizzati, banner e altre amenità. E se su YouTube la pubblicità è diventata praticamente un secondo contenuto da guardare, Reddit non sta facendo molto per distinguersi. Una soluzione incredibile a questo problema è Morphe, un progetto open source per Android, nato dalla separazione dal team di Revanced che permette di applicare patch alle applicazioni, modificandone direttamente il comportamento. Morphe interviene sugli APK delle applicazioni, applicando modifiche al bytecode per aggiungere funzionalità, rimuovere componenti indesiderati e personalizzare l'interfaccia. Non richiede nemmeno i permessi di root. Il funzionamento è abbastanza semplice: Si installa Morphe sul proprio dispositivo Android. Si seleziona l'applicazione da modificare, ad esempio YouTube. Si sceglie la modalità di patching: Simple, con impostazioni predefinite, oppure Expert, per selezionare e configurare manualmente le singole patch. Morphe ti guiderà nel recupero dell'APK originale, applicando poi le modifiche direttamente sul dispositivo e generando una nuova versione dell'app da installare. Per quanto riguarda YouTube, si possono rimuovere le pubblicità nel feed e durante la riproduzione, integrare SponsorBlock per saltare automaticamente i segmenti sponsorizzati inseriti dagli autori dei video, ripristinare il contatore dei dislike e personalizzare parecchi elementi dell'interfaccia. Ma non c'è soltanto YouTube, Morphe supporta anche YouTube Music e Reddit, con patch specifiche per ciascuna applicazione. Il progetto prevede inoltre la possibilità di aggiungere sorgenti di patch compatibili mantenute dalla community, quindi il supporto si sta estendendo a macchia d'olio anche ad altre applicazioni, come Instagram e Facebook Il codice è pubblico, il patching avviene localmente e non vengono caricati APK o dati personali sui server del progetto, le patch ufficiali sono sicure, per quelle della community và invece sempre usato un occhio più attento. Reddit: r/MorpheApp Sito ufficiale: morphe.software GitHub: MorpheApp/morphe-manager

Welcome to r/wawona! Introduce Yourself & Start Here! 👋 Hey everyone! I’m Alex Spaulding (u/BigMacCircuits), founder of the Wawona Organization and lead developer of Wawona Compositor. Welcome to r/wawona! I’m excited to finally have a place where we can come together, share ideas, discuss development, and build a community around Wawona. For those who are new, Wawona is an open-source, cross-platform Wayland compositor that aims to bring Linux graphical applications to operating systems like macOS, iOS, and Android. The idea behind Wawona is pretty simple. I want to make it easier to run Linux applications on other operating systems without having to rely on a traditional Linux desktop environment. There’s a lot of interesting work involved in making that possible, especially when it comes to graphics, window management, input handling, and integrating with each platform. It’s an ambitious project, and there’s still plenty to figure out. That’s part of what makes it exciting! 🛠️ What to Post This subreddit is for anyone interested in Wawona, Wayland, Linux applications, and cross-platform development. Feel free to share: Development updates: Progress, experiments, and technical discoveries. Questions: Anything about Wawona, Wayland, or how the project works. Screenshots and demos: Show us what you’re working on or experimenting with! Bug reports and feedback: Found something that doesn’t work? Let us know. Ideas and suggestions: Have a feature in mind or an idea worth exploring? We’d love to hear it. Contributions: Code, documentation, testing, and anything else that helps move the project forward. You don’t have to be a developer to participate. If you’re interested in the project, you’re more than welcome here! ❤️ Community Vibe One thing that’s important to me is building a community where people feel comfortable asking questions, sharing their work, and expressing their ideas. Open-source development works best when people can collaborate, learn from each other, and have constructive discussions. It’s perfectly fine to disagree or question technical decisions. Just be respectful of one another. We’re all here because we enjoy technology and want to see what we can build together. 🚀 How to Get Started Introduce yourself! Tell us a little about yourself and what brought you here. Start a conversation! Ask a question, share an idea, or tell us what interests you about Wawona. Invite others! Know someone interested in Wayland, Linux, macOS, iOS, Android, or open-source software? We’d love to have them. Get involved! If you’re interested in contributing to development, testing, documentation, or even helping moderate the subreddit, feel free to reach out. 🌎 What’s Next? There’s a lot I want to accomplish with Wawona, and I’m looking forward to sharing that progress with everyone here. My hope is that this community becomes a place where people can follow development, contribute their own ideas, help solve problems, and maybe even discover something new along the way. Wawona is still growing, and I’d love for the community to grow alongside it. Thanks for being here and supporting the project, especially those of you joining us early on. I’m really looking forward to getting to know everyone! Welcome to r/wawona! 💙 Alex Spaulding (u/BigMacCircuits) Founder, Wawona Organization Lead Developer, Wawona Compositor

🇷🇺 Moscow. WordPress security research plugin developed by HERE IS LEO. It demonstrates advanced attack vectors, persistence mechanisms, and evasion techniques used in modern cyber threats. "For educational and research purposes only" here-is-leo/Moscow

团队里人人都被 issue 和 PR 打断，dsh-superagent 让一个 agent 守着整个 GitHub 仓库，请求来了它自己开工单、自己在独立会话里写完、回原对话交 PR，人的注意力只花在面板上那几件非人不可的事上。 deepseek-ai/dsh-superagent-prototype

uni.style - a new compile-time CSS library for ClojureScript and Clojure whimsicalCode/uni.style preview.redd.it

evot 已经能自主跑一个 PR 十几个小时：先提 draft，再用 computer use 按需调用远程 EC2，自己编译、部署，跑多套测试集验证正确性和性能。发现问题就修，修完再跑一轮，live: databend#20945

pc bios 16 bit github.com/bro732965-oss/bootpoot/tree/main

i fixed all there bullshit ads i blocked all their ads and the popups for time-frames you cant use the new forced block that says subscribe now also just annoyances i got the answer working on it update blocker done go grab it if you want md3222/tradingview-de-nag

自分の検証結果だとエラー起こすテストがあったので指摘したら直してくれたみたい。PR投げれなかったけどまぁalibaba-token-planのバグ直るならいっかー hermes-agent#148151

我修改过这个 cargo 版本可以很好的控制 target 无限增长，用了各种技巧来控制，专门为 AI 开发，多项目多 worktree 的场景来设计。 这个是我的 MacBook 上的情况，也是一直没删除过。 另外，这个工具是 NSH 写的：huacnlee/disktree 可以试试。 huacnlee/cargo huacnlee/disktree t.co

I built Drama Studio TTS engine using Fish Audio’s 35B Drama 3 speech model running locally on Apple silicon. Hand-written Metal kernels, Core ML audio codec, native Mac app, HTTP API and MCP server. Code: maralski/drama-studio