Topic

#automation

Loot, blog posts and adjacent themes connected to this topic. Follow the tag to keep it in your orbit.

#automation
#ai agents#developer-tools#open-source#free#github-copilot#agents#cli#ai-generated
Loot

More from this topic

Explore all loot
Scrape Changing Websites with Anansi Self-Healing Selectors and MCP

Scrape Changing Websites with Anansi Self-Healing Selectors and MCP

0
#web scraping#mcp+5
A Python crawler for unstable or JavaScript-heavy sites, with selector healing, structured-data extraction, adaptive rate limiting, and an MCP server for agent-driven crawling. Use only for authorized scraping. Anansi is a Python web scraping toolkit designed for sites that change often or need browser rendering. It combines adaptive parsing, structured-data extraction, incremental crawling, proxy support, and an MCP server so an LLM or agent workflow can drive fetch, extract, crawl, pause, resume, export, and metrics actions. Why it is useful Self-healing selectors: stores selector confidence and attempts fallback strategies when a layout changes. Structured extraction first: pulls JSON-LD, Open Graph, and Microdata before relying on brittle CSS selectors. Browser upgrade path: can switch from HTTP fetching to Playwright rendering for JavaScript-heavy pages. Crawler durability: includes an async crawler, SQLite-backed queue, incremental recrawls, ETag/Last-Modified handling, and resumable jobs. Agent-ready interface: ships with an MCP server so compatible LLM tools can operate crawls through tool calls. Best fit Use Anansi when you need a resilient research or data-extraction crawler for websites you are allowed to access, especially where pages change structure or require JavaScript rendering. It is most relevant for developers building data pipelines, monitoring workflows, competitive research dashboards, or agentic browsing systems. Quick evaluation checklist Confirm the target website permits your intended crawling use case. Start with structured data extraction before custom selectors. Enable browser rendering only where HTTP fetching is insufficient. Keep adaptive rate limiting active and respect Retry-After responses. Use the MCP server when you want an agent to orchestrate crawl tasks instead of manually scripting every step. Source notes The GitHub repository describes Anansi as a self-healing web scraper with selector repair, browser rendering fallback, Chrome-like TLS fingerprinting, Pydantic validation, incremental crawling, and an MCP server. The project is written primarily in Python and is licensed under Apache-2.0.
Free
Review open
0
Open loot
Test Cloudflare Browser Run requests before wiring a Worker

Test Cloudflare Browser Run requests before wiring a Worker

0
Text: AI-generated
#ai-generated#automated+6
AI-generated · Automatically published by LinkLoot. Cloudflare's new Browser Run Playground lets developers trial screenshots, PDFs, extraction, and AI-structured scraping from the dashboard before writing integration code. AI-generated: This Loot was created and published automatically by LinkLoot and was not substantively reviewed by a human editor. What it is Cloudflare Browser Run now has a dashboard Playground for testing Quick Actions against a live browser. You can submit a URL or raw HTML, adjust viewport and page-load settings, preview output, and copy working request code. Who it helps It is useful for developers building browser automation, scraping, QA capture, agent browsing, or document-generation workflows on Cloudflare. It reduces setup time when you need to prove that a page can be captured, parsed, or turned into structured data before creating a Worker. How to evaluate it Start with a non-sensitive URL, test screenshots or Markdown extraction, then compare the copied request against the Browser Run Quick Actions documentation. If you use AI extraction, test with a small JSON schema first so costs and output shape are visible before adding it to a production flow. Limits and risks The Playground is not a free sandbox. Cloudflare says Playground requests incur Browser Run charges, and AI extraction also incurs Workers AI charges. Treat target pages as untrusted input, avoid submitting secrets, and check site terms before automating extraction at scale. Sources Cloudflare changelog
Free
Review open
0
Open loot
Run a company-scoped multiplayer agent harness with QM

Run a company-scoped multiplayer agent harness with QM

0
Text: AI-generated
#agents#developer-tools+7
AI-generated · Automatically published by LinkLoot. QM is an open-source agent harness for teams that want Slack, web, scoped memory, durable sandboxes, and model choice without tying the whole workflow to one vendor. AI-generated: This Loot was created and published automatically by LinkLoot and was not substantively reviewed by a human editor. QM is worth a cautious look if your team wants agents to work across shared rooms, personal workspaces, Slack, and web surfaces without turning every employee's assistant into a separate unmanaged project. What it is QM is an open-source multiplayer agent harness from yc-software. Its README describes a company-oriented setup where each person and each room can have scoped memory, files, permissions, crons, web apps, and a durable sandbox. Who it helps It fits startups and technical teams experimenting with collaborative agents: shared project channels, internal app generation, repository work, scheduled watches, and company knowledge retrieval. The project explicitly supports multiple harnesses and models, including Pi, OpenCode, Codex, and Claude Code. How to evaluate it Start with the README and deployment docs before running anything. Check the deployment target, required credentials, Slack access, sandbox isolation model, and command policies. The project exposes an npm-based init flow, but a production trial should happen in a separate cloud account or isolated test workspace first. Limits and risks QM is infrastructure, not a small browser tool. It touches identity, credentials, command execution, persistent memory, and shared workspaces. Review SECURITY.md, inspect the deployment layer, and decide how strict approvals should be before connecting real services. Access and pricing The repository is public and lists an MIT license. Hosting, model usage, Slack, database, and cloud runtime costs remain your responsibility. Sources QM GitHub repository Hacker News discovery thread
Free
Review open
0
Open loot
Check suspicious links in OpenClaw with domain-trust-check

Check suspicious links in OpenClaw with domain-trust-check

0
Text: AI-generated
#openclaw#security+5
AI-generated · Automatically published by LinkLoot. An OpenClaw security skill that checks URLs and domains for phishing, malware, brand abuse, and scams through the Outtake Trust API. Use it before visiting links from email, chat, scraped pages, or support tickets; it returns a verdict, confidence score, safe-to-visit flag, and recommended action. Requires an OUTTAKEAPIKEY. AI-generated: This Loot was created and published automatically by LinkLoot and was not substantively reviewed by a human editor. Use this when an OpenClaw agent needs to inspect a link before opening it or recommending it. The skill checks a single URL or a batch of up to 50 URLs through the Outtake Trust API and returns a structured verdict with confidence, safe-to-visit status, and recommended action. Best fit: email triage, support-ticket review, scraped lead lists, and suspicious domains shared in chat. Requires an OUTTAKEAPIKEY.
Free
Review open
0
Open loot
Use OfficeCLI to Give Agents a Local Handle on Word, Excel, and PowerPoint

Use OfficeCLI to Give Agents a Local Handle on Word, Excel, and PowerPoint

0
#office#automation+4
An open-source command-line Office toolkit for agents that need to inspect, render, and edit DOCX, XLSX, and PPTX files without a desktop Office install. OfficeCLI is a practical bridge for agent workflows that need to work with Microsoft Office files instead of plain text. It gives command-line agents a way to read, create, edit, render, and automate Word, Excel, and PowerPoint documents locally. The strongest fit is document-heavy automation: checking slide decks, extracting spreadsheet structure, generating reports from templates, rendering files to HTML or PNG for visual review, and letting an agent make another pass after it sees the output. Why it is useful now: It is open source under Apache-2.0. The project publishes standalone binaries for Windows, macOS, and Linux. Recent releases include checksum files, which makes it easier to verify downloaded binaries. The repository targets agent clients and workflows, including Codex, Claude Code, and OpenClaw-style automation. Use it when the task needs structured Office-file operations that normal text extraction cannot handle. Avoid treating it as a complete replacement for human review: Office formats are complex, layout fidelity can matter, and generated documents should still be checked before client delivery. Source notes: the GitHub repository is the primary source for licensing, binaries, and releases. Trendshift is included only as an external discovery signal, not as proof of quality or safety.
Free
Review open
0
Open loot
Add macOS mouse gestures with StrokeMouse

Add macOS mouse gestures with StrokeMouse

0
#macos#productivity+4
StrokeMouse is an open-source macOS menu bar utility for binding mouse gestures to shortcuts, app launches, window actions, media keys, URLs, Shell commands, and AppleScript. StrokeMouse is a local macOS gesture utility for people who want faster window and app control without buying into a closed automation stack. Each gesture can use its own trigger button, such as right, middle, or side click, and can run globally or only inside selected apps. The useful angle is the action range: shortcuts, app launching, URLs, media keys, window commands, Shell, and AppleScript are all supported. Gesture configs can be imported or exported as JSON, which makes it practical to keep a repeatable setup across machines. Check the caveats before installing. The app needs macOS Accessibility permission for global mouse capture and shortcut/window actions. The current GitHub release notes say the builds use a stable self-signed identity rather than Apple Developer ID notarization, so macOS may require right-click Open or Privacy & Security approval. Treat Shell and AppleScript actions like any local automation: only run commands you wrote or trust. Best fit: macOS power users, creators, developers, and ops people who want gesture-driven app/window automation with source visibility. Skip it if you need notarized enterprise deployment or a fully polished commercial support path today.
Free
Review open
0
Open loot
Control Audacity from MCP clients with Audacity-MCP

Control Audacity from MCP clients with Audacity-MCP

0
#audacity#mcp+4
A local MCP server that lets compatible AI clients drive Audacity audio-editing workflows through Audacity's scripting interface. Audacity-MCP is a practical bridge for creators who already edit in Audacity and want an MCP-compatible assistant to help with repeatable audio work. The project packages a Python MCP server for Audacity via mod-script-pipe, so the useful angle is not another cloud audio editor; it is local control of an existing desktop editor from clients that can speak MCP. Use it when you want to experiment with assistant-driven podcast cleanup, voiceover editing, transcription labels, export steps, or mastering prep while keeping the audio workflow anchored in Audacity. The PyPI package currently lists audacity-mcp as a beta Python package for AI-driven audio editing via mod-script-pipe and requires Python 3.10 or newer. Evaluation notes before using it in production: Treat it as a beta tool and test on copied project files first. Audacity must support the scripting path the tool relies on; check Audacity's own scripting documentation before setup. Review the install scripts and dependencies before running them on a creator workstation. Do not assume the assistant's audio choices are final; keep human listening and export QA in the loop. Good fit: podcasters, video editors, musicians, and automation builders who want to turn repeated Audacity actions into promptable local workflows without uploading raw audio to a hosted editor.
Free
Review open
0
Open loot
Run longer agent jobs with DeerFlow before handoffs lose context

Run longer agent jobs with DeerFlow before handoffs lose context

0
#ai-agents#developer-tools+5
An open-source super-agent harness for research, coding, sub-agents, memory, sandboxes, and skills. What it is DeerFlow is ByteDance's open-source super-agent harness for longer jobs that need more than a single chat turn. It combines sub-agents, memory, sandboxes, skills, and a message gateway so an agent can research, code, create artifacts, and continue work across multi-step sessions. Who should use it Use it if you are evaluating agent infrastructure for deep research, coding workflows, report generation, or multi-agent task execution. It is most relevant for builders who already understand the cost and risk of letting agents use tools, files, shells, or browser/search providers. How to evaluate it Start with the official repository and installation guide. Run it locally or in Docker before exposing it to shared users. Use make setup and make doctor to generate config and catch setup problems. Test one contained workflow first: research summary, codebase inspection, or document generation. Keep sandbox mode and provider limits tight until you understand the execution path. Limits and risks DeerFlow is powerful because it can coordinate tools, models, files, and sub-agents. That also means misconfiguration can create security risk. Review the .env, model-provider config, shell/file-write permissions, sandbox settings, and any skill code before running it on sensitive projects. The repo also notes that DeerFlow 2.0 is a ground-up rewrite, so teams using older DeerFlow material should check whether guidance applies to the current branch. Source links Primary source: https://github.com/bytedance/deer-flow Discovery/context: https://github.com/topics/ai-agents
Free
Review open
0
Open loot
Build X bots with Vercel Chat SDK

Build X bots with Vercel Chat SDK

0
#vercel#chat-sdk+3
Use Vercel Chat SDK's new X adapter to handle public mentions and direct messages from one bot codebase. Vercel added an X adapter to Chat SDK on July 14, 2026. It lets teams build bots that reply to public mentions and direct messages through X API v2 and the X Activity API while keeping the same Chat SDK pattern used for Slack, Discord, GitHub, Teams, Telegram, and WhatsApp. Best fit: teams already building multi-channel support, community, or workflow bots with Chat SDK. Check before use: The adapter handles CRC verification, webhook signature checks, and OAuth token refresh for long-running bots. X supports likes as the only reaction in this adapter. Responses post once after completion because X has no native streaming. X automation rules still apply to automated messages, so review policy and rate limits before production use.
Free
Review open
0
Open loot
Repair Vercel build settings from the CLI before redeploying

Repair Vercel build settings from the CLI before redeploying

0
#vercel#cli+3
Use Vercel CLI project update to fix framework presets, build commands, output directories, and auto-detection without opening the dashboard. Vercel now lets teams update project framework and build settings from the terminal with vercel project update. It is most useful when an agent or CI helper has diagnosed a failed deployment and needs to correct the framework preset, build command, install command, development command, or output directory before redeploying. Try it when a project was imported with the wrong preset, a monorepo output path changed, or a dashboard-only fix would slow down an automated recovery flow. Use --format=json when another script needs to inspect what changed, and use --auto-detect when you want Vercel to resume automatic detection for a setting. What to check first: Update the Vercel CLI to v54.21.1 or later. Confirm the linked project or pass the project name explicitly. Review changed settings before redeploying production. Do not pipe secrets into build settings; keep secret values in environment variables. Example use cases: Fix a Vite-to-Next.js preset mismatch. Reset a stale output directory to auto-detection. Let an agent repair build settings using JSON output for verification.
Free
Review open
0
Open loot
Make Cloudflare Workflows retry around rate limits instead of fixed timers

Make Cloudflare Workflows retry around rate limits instead of fixed timers

0
#cloudflare#workflows+4
Cloudflare Workflows now lets each step calculate its next retry delay from the failed attempt and error, useful for rate limits, Retry-After handling, and flaky downstream APIs. Cloudflare added dynamic retry delays to Workflows on July 9, 2026. Instead of picking only a fixed delay plus constant, linear, or exponential backoff, a Workflow step can now pass a function to retries.delay and calculate the next wait from the current attempt and the thrown error. Use this when a workflow calls APIs with different failure modes: wait longer on rate-limit errors, retry faster after a short network failure, or map provider guidance such as Retry-After into your next delay. This is a practical fit for customer sync jobs, AI-provider orchestration, payment/CRM integrations, and any durable workflow that should avoid both blind hammering and unnecessary waiting. Check before using Confirm your Workflow code is using the current Cloudflare Workflows API and docs. Treat error-message matching as a fallback; prefer structured error data when your SDK exposes it. Add a maximum retry count and clear terminal-error path so bad credentials or malformed payloads do not loop. Test against one intentionally rate-limited API call before relying on it for paid providers. Sources Cloudflare changelog: dynamic retry delay support for Workflows. Cloudflare Workflows docs: sleeping, retrying, and the retries.delay function shape.
Free
Review open
0
Open loot
Cap GitHub Copilot CLI agent spend with AI credit session limits

Cap GitHub Copilot CLI agent spend with AI credit session limits

0
#github-copilot#cli+4
GitHub Copilot CLI and the Copilot SDK now support per-session AI credit limits, giving developers a practical guardrail for long-running agent tasks and unattended automation. What it does GitHub added AI credit session limits for Copilot CLI and the Copilot SDK. The practical value is simple: before you hand an agent a long task, you can set a credit cap so the session stops cleanly instead of running until the work is done or someone notices the bill. This belongs in a developer's automation checklist because AI coding agents are increasingly used for unattended refactors, test runs, investigations, and SDK-driven workflows. A per-session cap does not replace account budgets, but it gives each run a local spending boundary. How to try it Update GitHub Copilot CLI to version 1.0.66 or later, then use the new session-limit controls before starting work. For interactive CLI sessions, GitHub's docs show the /limits set command: For non-interactive CLI jobs, pass a maximum credit value on the command line: GitHub notes that the limit is a soft cap: a model response already in progress can finish, so final usage may slightly exceed the number you set. Their docs also advise that session limits work best above 30 AI credits because many model calls can cost more than 20 credits. Best use cases Budgeting unattended Copilot CLI jobs in CI-like local automation. Running exploratory codebase tasks without leaving an agent unbounded. Testing prompt cost before scaling a workflow across a team. Giving SDK-based agent features a per-run guardrail. Caveats This is a public preview feature, so behavior may change. It also controls a single session only; teams still need organization budgets, billing alerts, model-selection policies, and human review for expensive agent workflows. Treat the first few runs as calibration. Start with small, reversible tasks, check actual AI credit use afterward, and adjust the limit based on prompt size, repository size, selected model, and tool-call depth. Source links GitHub Changelog: https://github.blog/changelog/2026-07-01-set-ai-credit-session-limits-in-copilot-cli-and-sdk/ GitHub Docs: https://docs.github.com/en/copilot/tutorials/optimize-ai-usage GitHub CLI best practices: https://docs.github.com/copilot/how-tos/copilot-cli/cli-best-practices Session limit setup docs: https://docs.github.com/en/copilot/how-tos/copilot-cli/use-copilot-cli/set-session-limit
Free
Review open
0
Open loot
Use GitHub CLI to Read Repo Files Without Cloning

Use GitHub CLI to Read Repo Files Without Cloning

0
#github-cli#developer-tools+4
GitHub CLI 2.95.0 adds preview commands for reading files and directories from remote repositories, useful for agents, audits, and quick config checks. Why this is useful GitHub CLI 2.95.0 adds gh repo read-file and gh repo read-dir, two preview commands for inspecting repository content directly from the terminal. It is a practical upgrade for developers, maintainers, and AI-agent workflows that need to check a README, config file, package manifest, docs folder, or policy file without cloning the full repository first. Quick start Caveats The commands are marked preview, so flags or output details may change. Access still follows the permissions of the authenticated GitHub user, and large or binary files are not a replacement for a proper checkout. For automation, pin your expected gh version and handle missing-command fallback paths. Source check Source What it confirms --- --- GitHub Changelog gh repo read-file and gh repo read-dir are available in GitHub CLI 2.95.0+ GitHub CLI release notes The release date, examples, preview status, and scripting flags GitHub CLI manual Exact command syntax, JSON fields, and terminal escape-sequence behavior
Free
Review open
0
Open loot
LinkLoot preview for Workflow Tools for OpenClaw: Loop Checks, Parallel Decisions, and File-Size Review

Workflow Tools for OpenClaw: Loop Checks, Parallel Decisions, and File-Size Review

0
#openclaw#skill+5
An OpenClaw skill candidate that bundles TODO/FIXME loop scans, parallel-vs-serial planning, file-size review, and subworkflow handoff into one local workflow surface. What it does Workflow Tools is an OpenClaw community skill candidate for keeping agent work tidy before it drifts. The skill defines a /wt command surface for four workflow utilities: scanning directories for open loops such as TODO/FIXME/PLACEHOLDER markers, evaluating whether a task should run in parallel or serial, checking files against a line-count threshold, and handing a task to another installed ClawHub skill. Pricing classification: free. The reachable Live Neon source repository is public and reports an MIT license; no paid gate was visible in the checked sources. Who should use it Use this candidate for review if your OpenClaw workspace often accumulates unfinished markers, oversized files, unclear handoffs, or parallelization decisions that need a repeatable checklist. It fits operators who want lightweight local workflow hygiene rather than another external SaaS integration. Setup surface The skill declares config files under .openclaw/workflow-tools.yaml and .claude/workflow-tools.yaml, plus output folders under output/loops/, output/parallel-decisions/, output/mce-analysis/, and output/subworkflows/. Its own text says loop scans and file-size review can read user-specified paths, and subworkflow mode can invoke other installed ClawHub skills. No installation or execution was performed on this Raspberry Pi. Runner test plan Static scan: inspect the Awesome entry, ClawHub page, Clawskills listing, mirrored SKILL.md, Live Neon source tree, raw SKILL.md, license file, and any repository metadata without executing commands. Dependency/install review: verify whether the skill has executable scripts, package manifests, hidden dependencies, install hooks, generated assets, or required companion skills such as failure-memory and constraint-engine. Prompt-injection/tool-poisoning review: check the SKILL.md and examples for instruction override attempts, secret requests, broad file-reading defaults, unsafe delegation language, or attempts to bypass OpenClaw approvals. Sandbox execution: only after static approval, install in a disposable OpenClaw workspace with dummy files, restricted secrets, isolated output directories, and no production skills available for subworkflow delegation. Screenshot/video when UI or command output exists: capture terminal output for /wt loops, /wt parallel, /wt mce, and a blocked or dummy /wt subworkflow attempt so reviewers can verify behavior. Residual risks: document arbitrary path scanning, accidental exposure of sensitive files, noisy TODO false positives, subworkflow permission expansion, stale companion-skill assumptions, and drift between Clawskills mirror version 1.4.0 and Live Neon source version 1.5.0. Risk notes This Loot is a review candidate, not a safety endorsement. Community skill text is untrusted input. The most important risk is scope: /wt loops and /wt mce are useful because they read user-selected paths, but that same design can touch private code or config if pointed at the wrong directory. Subworkflow mode also inherits risk from whatever other skills are installed. Runner AI Review should verify behavior in a blank workspace before any real project, token, cookie, SSH config, or private repository is exposed. Source links Awesome OpenClaw Skills category entry: https://raw.githubusercontent.com/VoltAgent/awesome-openclaw-skills/main/categories/productivity-and-tasks.md ClawHub page: https://clawhub.ai/leegitw/workflow-tools Clawskills listing: https://clawskills.sh/skills/leegitw-workflow-tools Clawskills SKILL.md mirror: https://clawskills.sh/skills-markdown/leegitw/workflow-tools.md Underlying Live Neon source tree: https://github.com/live-neon/skills/tree/main/agentic/workflow-tools Raw SKILL.md source: https://raw.githubusercontent.com/live-neon/skills/main/agentic/workflow-tools/SKILL.md License evidence: https://raw.githubusercontent.com/live-neon/skills/main/LICENSE
Free
Review open
0
Open loot
LinkLoot preview for This Turns Any Coding Agent Into a Video Studio

This Turns Any Coding Agent Into a Video Studio

0
#AI Video#Coding Agents+4
A premium agent workflow for creating deterministic MP4 videos from plain HTML, CSS, media, and seekable animations.
29
Review open
0
Open loot
LinkLoot preview for Agent Browser for OpenClaw: Ref-Based Browser Automation Candidate

Agent Browser for OpenClaw: Ref-Based Browser Automation Candidate

0
#openclaw#skill+5
A high-utility OpenClaw skill candidate for deterministic browser automation using accessibility snapshots and ref-based element targeting. Not yet tested by Runner AI Review. What it does Agent Browser is an OpenClaw community skill candidate for controlling web pages through a dedicated browser automation CLI. Its useful angle is ref-based interaction: the agent takes an accessibility-tree snapshot, identifies stable element references, and then uses those refs for clicks, fills, extraction, screenshots, PDFs, saved sessions, and multi-session workflows. Pricing classification: free. Source evidence shows the underlying agent-browser package declares an Apache-2.0 license and the public repository exposes an Apache License file. Who should use it Use this candidate for review if you often need reliable browser workflows where CSS selectors are too brittle: multi-step forms, dynamic single-page apps, login-state reuse, parallel admin/user sessions, and structured extraction from web UIs. It is especially relevant for OpenClaw operators who want a CLI-style browser runner with reproducible command output. Setup surface The skill surface references a global agent-browser CLI and Chromium installation. That means the review should inspect the npm package, postinstall behavior, browser download path, required Node version, native binary handling, and any permissions implied by session state, cookies, storage, screenshots, PDFs, uploads, clipboard, network routing, JavaScript evaluation, and local files. No installation or execution has been performed on this Raspberry Pi. Risk notes This Loot is a candidate, not a safety endorsement. The skill and related pages are community-controlled untrusted content. The linked OpenClaw skills repository URL shown by directories was not used as executable evidence here; the reachable source evidence used for pricing and tooling context is the ClawHub/clawskills skill page, the clawskills skill markdown mirror, and the public Vercel Labs agent-browser repository/package files. Runner AI Review artifacts are still required before anyone should treat the skill as tested, safe, clean, recommended, or production-ready. Source links Awesome OpenClaw Skills list: https://raw.githubusercontent.com/VoltAgent/awesome-openclaw-skills/main/categories/clawdbot-tools.md ClawHub page: https://clawhub.ai/matrixy/agent-browser-clawdbot Clawskills listing: https://clawskills.sh/skills/matrixy-agent-browser-clawdbot Skill markdown source mirror: https://clawskills.sh/skills-markdown/matrixy/agent-browser-clawdbot.md Underlying tool repository: https://github.com/vercel-labs/agent-browser Package/license evidence: https://raw.githubusercontent.com/vercel-labs/agent-browser/main/package.json and https://raw.githubusercontent.com/vercel-labs/agent-browser/main/LICENSE
Free
Review open
0
Open loot
Blog

Related reads

Browse blog
AI & Automation

GPT-Live Rollout: Schedule, Availability and Access

Track the OpenAI GPT-Live rollout for ChatGPT Voice: availability, rollout schedule, who gets GPT-Live-1 or mini, and how to access it.

Tools & Apps

Count Cloudflare Workflows steps before August billing starts

Cloudflare Workflows now has per-step pricing in its billing model, with step and storage billing scheduled to start no earlier than August …

Tools & Apps

Cap Copilot agent spend before long CLI and SDK runs

GitHub Copilot now lets CLI and SDK users set AI credit limits per session, giving agent automation a soft spending cap before background wo…

AI & Automation

Use Claude Sonnet 5 for cheaper agent workflows before moving to Opus

Anthropic has launched Claude Sonnet 5 as a lower-cost agentic model for coding, tool use, and knowledge work, with API access, Claude Code …

Tools & Apps

Run GitHub Actions steps in parallel without losing separate logs

GitHub Actions now supports parallel steps with background, wait, wait-all, cancel, and parallel syntax. It is useful for faster CI jobs, bu…

AI & Automation

Mistral OCR 4 Adds Structured Output for Document AI Pipelines

Mistral OCR 4 brings bounding boxes, block classification, confidence scores, 170-language coverage, and self-hosting options to document ex…

AI & Automation

Hugging Face Shows How to Benchmark Whether Tools Are Agent-Friendly

Hugging Face published an agent-evaluation harness that tests whether coding agents can use a library efficiently, not only whether they rea…

AI & Automation

GitHub expands Copilot Agent Tasks API to paid individual plans

GitHub now lets Copilot Pro, Pro+, and Max users start and track Copilot cloud agent tasks through the Agent Tasks REST API. The practical v…

Tools & Apps

Novu Connect turns one AI agent into a multi-channel teammate

Novu Connect is a new Agent Communication Infrastructure layer for connecting Claude Managed Agents and custom agents to Slack, Microsoft Te…

Tools & Apps

VS Code 1.124 makes agent sessions easier to queue, navigate, and govern

Visual Studio Code 1.124 sharpens the Agents window with background sessions, keyboard navigation, restored layouts, smarter Autopilot, brow…

AI & Automation

GitHub Agentic Workflows Moves Into Public Preview

GitHub Agentic Workflows is now in public preview, letting teams define AI-driven repository automation in Markdown and run it through GitHu…

Deals & Freebies

Albato's AppSumo deal adds AI agents to no-code automation

Albato is back on AppSumo with a lifetime automation offer, and the June update adds Albato Copilot plus autonomous AI Agents for building a…

AI & Automation

Claude Fable 5: What Anthropic's Public Mythos-Class Model Changes for AI Workflows

Anthropic has released Claude Fable 5, its first generally available Mythos-class model, while keeping Claude Mythos 5 limited to approved p…

AI & Automation

Turn ChatGPT Into Your Homey Smart Home Control Panel

Homey is now available as a ChatGPT app, so users can connect their Homey account, control devices, start Flows, set Moods, and ask ChatGPT …

AI & Automation

Microsoft Build 2026 puts agent context, Scout, and MAI models into one developer stack

Microsoft used Build 2026 to frame its agent platform around Microsoft IQ, the Scout personal agent, new MAI models, Frontier Tuning, Agent …

Tools & Apps

GitHub Copilot app opens wider as Copilot CLI adds scheduled prompts

GitHub widened the Copilot app technical preview to existing paid Copilot customers and updated Copilot CLI with experimental scheduled prom…

AI & Automation

Microsoft Build 2026 Puts Agent Controls Into Policy Files

Microsoft's Build 2026 agent stack centers on ASSERT, Agent Control Specification, and Agent 365 controls for safer production agents.

AI & Automation

Microsoft Build 2026 puts agent containment into Windows

Microsoft used Build 2026 to push Windows toward governed agent execution with MXC, Windows 365 for Agents and local AI APIs.

Tools & Apps

Firecrawl /monitor pings AI agents only when watched web pages change

Firecrawl /monitor gives AI agents signed webhooks and structured diffs when watched pages or sites change, reducing repeated scraping loops…

AI & Automation

Open Envelope proposes a portable schema for AI agent teams

Open Envelope is positioning an Apache-licensed schema for AI agent teams as a portable way to define roles, handoffs, schedules, access pol…

Business & Karriere

Claude Managed Agents add dreaming, outcomes, and multiagent orchestration

Anthropic has expanded Claude Managed Agents with dreaming, outcomes, multiagent orchestration, and webhooks, pushing the platform toward lo…

AI & Automation

Google A2UI gives agents a safer way to render interactive interfaces

Google has made A2UI public as an open project for agent-driven user interfaces, giving AI agents a declarative way to request rich UI witho…

AI & Automation

Proton Pass adds access tokens for AI agents

Proton Pass now offers AI access tokens so users can share selected credentials with agents while applying permissions, time limits, and aud…