- zahT3 (@zahT3zuo) on X
Hotseat is a free, open-source macOS menu bar app that moves Claude Code and Claude Desktop to another of the user's Claude accounts in one click and returns to the same session. Sessions, settings, skills and MCP servers are shared, so `claude --resume` works under either account. When a session hits a usage limit, it offers to continue under another account. It never reads tokens or cookies. Install with Homebrew.
x.comtoolAdded 1 Nov 2026, published 31 Oct 2026🧠 AI - Prasenjit Sarkar (@stretchcloud) on X
A thread on Cloudflare's agent-readiness scan and the AgentReady.org open spec for "Agent Experience", developed with Vercel, Stripe, Auth0, Mintlify, Google, Netlify and Elementor. The scan grades whether agents can find a site (robots.txt, DNS), read clean Markdown, pass bot rules, and discover an MCP server or API catalog. One quoted example raised a score from 20 to 67 by shipping an API catalog with Link headers, an MCP server card, a skills index and an AI catalog file.
x.comthreadAdded 30 Oct 2026, published 29 Oct 2026🧠 AI - rohitg00/ai-engineering-from-scratch
ai-engineering-from-scratch is a free, MIT-licensed curriculum of 542 lessons in 20 phases, from math and deep learning through transformers, LLM engineering, MCP, agents and capstones. Code is in Python, TypeScript, Rust and Julia. It includes three graded projects (retrieval evaluation, agent trace debugger, tool call firewall), installable tutor skills for Claude Code and Codex, and certification prep tracks.
github.comcourseAdded 29 Oct 2026🧠 AI
Eddy (@ieddysun) on XExpo's official skills package gives AI coding agents scoped instructions for building Expo apps. One command, npx skills@latest add expo/skills --skill '*', installs it for Cursor, Copilot and Windsurf, while Claude Code and Codex use their plugin marketplaces. Skills include expo-router, expo-animation, expo-upgrade and eas-update. The Expo MCP server adds live docs lookup, compatible dependency installs, EAS build monitoring and simulator screenshots.
x.comthreadAdded 29 Oct 2026, published 28 Oct 2026🧠 AI- Laban (@lunkertw) on X
An X post summarising five AI items: Google DeepMind's Gemini 4 Carbon (88.2% SEC-bench Pro, 54.8% ExploitGym, 71.0% CWE-bench, 59 on Artificial Analysis Intelligence Index v5.0), Ed Zitron's critique of Anthropic's S-1, a Utah Claude Code pilot, and the repos beenuar/AiSOC and expo/skills. In the Utah pilot, 34 developers in 10 agencies took part over four weeks, 80% had a working setup within 30 minutes, and 71% saved over 20 hours. It gives short summaries and links, not primary analysis.
x.comthreadAdded 29 Oct 2026, published 28 Oct 2026🧠 AI - alex shapalov (@alxshp) on X
PGX is a free, open-source Postgres runtime written in Rust that hosts thousands of isolated databases in one process, aimed at AI agents. A companion agent skill, installed with `npx skills add pgrundev/pgx --skill pgx`, gives each Claude Code agent its own database automatically. The author claims 1,000 databases in 659 MB RAM, about 0.7 MB per idle database, an 85 ms clone of a 674 MB database, and a 200-agent test with no conflicts.
x.comtoolAdded 28 Oct 2026, published 27 Oct 2026🧠 AI
Interpretable Meta-Policies for Neural Decision MakingNEXUS is a hierarchical reinforcement learning framework that pairs neural skills with symbolic meta-policies, so transparent reasoning sits at the level of high-level skills rather than atomic actions. It uses object-centric observations and LLM interaction to design reward functions and meta-policies. Agents learn disentangled skills, align better with goals in the game manual, resist reward hacking more, and cope better with game simplifications than deep RL. The paper also compares neural, symbolic and neuro-symbolic meta-policy architectures.
arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI- Manoj | The AI Dude (@Manojkumar2257) on X
heditor is an open-source (MIT) agent skill from pycodebr that has Claude Code, Codex, Cursor or OpenCode edit talking-head videos. It transcribes with faster-whisper, picks a 30-70s segment, cuts frame-accurately, builds HTML + GSAP motion graphics, mixes audio at -14 LUFS, and runs QA with vision-reviewed previews. It offers 42 named styles and a long-form mode with chapters, SRT/VTT and lower thirds. Install: npx skills add pycodebr/heditor -g.
x.comthreadAdded 28 Oct 2026, published 27 Oct 2026🧠 AI - Search Search results for "security" | MCP Market
MCP Market search results for "security" in its skills category, listing about 20 installable AI agent skills. Entries cover OWASP Top 10 audits, secure PHP coding, STRIDE threat modeling, CVE remediation, security header analysis, misconfiguration finding, bug bounty triage and AgentShield scans of Claude Code configurations. One is a paid D365FO security-role XML skill. Each entry has only a one-line description and a category label.
mcpmarket.comtoolAdded 25 Oct 2026🧠 AI - alirezarezvani/claude-skills
claude-skills is an MIT-licensed library of about 398 Claude Code skills, agents, personas and plugins across 20 domains, including engineering, marketing, compliance and C-level advisory. Each skill is a SKILL.md with stdlib-only Python CLI tools and reference docs. Install scripts and convert.sh adapt it to Codex, Gemini CLI, Cursor, Aider, Windsurf and other coding agents, and it includes a skill-security-auditor scanner.
github.comrepoAdded 25 Oct 2026🧠 AI - Search Search results for "security" | MCP Market
MCP Market search results for "security" in the skills category, listing about 20 installable AI agent skills. Entries cover OWASP Top 10 audits, secure coding for PHP, STRIDE threat modeling, CVE remediation, security header analysis, misconfiguration finding, bug bounty triage and AgentShield scans of Claude Code configurations. One is a paid D365FO security-role XML skill. Each entry has only a one-line description and a category label.
mcpmarket.comotherAdded 25 Oct 2026🛡️ Security - alirezarezvani/claude-skills
claude-skills is an open-source MIT library of about 398 Claude Code skills, agents and plugins that also installs into Codex, Gemini CLI, Cursor and 9 other coding agents. The security-relevant parts are skill-security-auditor, a stdlib-only Python scanner that checks skills for command injection, data exfiltration, prompt injection and dependency supply-chain risks before install, plus a security-guidance PreToolUse hook, a security suite and compliance skills (ISO 27001, SOC 2, GDPR).
github.comrepoAdded 25 Oct 2026🛡️ Security - Gökdeniz Gülmez (@ActuallyIsaak) on X
An X post showing how to have Codex train a small model on Apple silicon through the mlx-lm-lora MCP server and skill. It gives five setup steps (pip install with the mcp extra, npx skills add, locate mlx-lm-lora-mcp, codex mcp add). The prompt runs four pre-training trials on tiny-random/qwen3 with the mlx-community/recycling_the_web-1k dataset. Codex picks the optimizer and learning rate itself, and the result is a table with validation loss and the best adapter path.
x.comthreadAdded 25 Oct 2026, published 24 Oct 2026🧠 AI
affaan-m/ECC | RepoDirECC (affaan-m/ECC) is an open-source performance optimization system for AI coding agents. It packages 261+ skills, 64+ agents and 84+ commands that tune Claude Code, Codex, Cursor and other agent harnesses for speed, memory and security. Practitioners can use it as a ready-made skills and harness configuration set. The RepoDir page gives only this short description, with no install steps or benchmarks.
repodir.comrepoAdded 24 Oct 2026🧠 AI
EveryDev.ai (@EveryDevAi) on XToolUniverse, from ScientistTools, is an open-source (Apache-2.0) toolkit that gives any LLM one interface to more than 1,000 scientific tools, models and databases such as PubMed, UniProt and ChEMBL. It ships a native MCP server, a Python SDK and a tu CLI, plus 68 pre-built agent skills. The post says it works with Claude Code, Cursor, Gemini CLI and Windsurf.
x.comthreadPublished and added 24 Oct 2026🧠 AI
4DMemory: Benchmarking Long-Horizon Spatiotemporal Memory with Harness-Augmented Agents4DMemory is a benchmark suite for long-horizon spatiotemporal memory: the LongVideo dataset (about 900 hours of video, over 5,000 manually reviewed questions) and 4DMemoryBench. It also presents the 4DMemory Harness, combining four skills, 22+ tool models and a model-specific RAG system. Across 13 models, the harness improved every one by over 50%, and the same models scored over 10% lower than on a previous benchmark.
arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🧠 AI- Donating Agent Skills to the Agentic AI Foundation
Simon Willison's link post covers Anthropic's 22 October 2026 announcement that it is donating the Agent Skills standard to the Agentic AI Foundation (AAIF) under the Linux Foundation. Anthropic co-founded the AAIF with Block and OpenAI and earlier donated MCP to it. Willison notes he predicted this in December 2025 and found his old post by querying his blog through datasette-mcp in Claude.
simonwillison.netarticlePublished and added 22 Oct 2026🧠 AI
How bug bounty sharpens one researcher’s security skillsGitHub Bug Bounty spotlight interview with @r31n, a researcher known for GitHub Enterprise Server findings. They describe a source-and-sink approach to mapping trust boundaries, chaining minor bugs (open redirect plus allowlisted SSRF that follows redirects), and confirming a finding only with a working PoC. They also cover using AI for code navigation and PoC scripts, and treating model output as untrusted input.
github.blogarticlePublished and added 22 Oct 2026🛡️ Security- SnailSploit/Claude-Red
claude-red is an MIT-licensed library of offensive security skills for the Claude Skills system, planned at about 130 skills across 23+ categories (web, Active Directory, cloud, exploit development, EDR evasion and others). Each skill is a SKILL.md file that loads on conversational triggers, so unused skills cost no context. It installs by git clone, sparse checkout per category, install.sh or pasting into a system prompt.
github.comrepoAdded 22 Oct 2026🧠 AI - SnailSploit/Claude-Red
claude-red is a library of offensive security skills for the Claude Skills system, each a SKILL.md file that loads on conversational triggers (for example, mentioning SQL injection loads offensive-sqli). Categories include web, Active Directory, cloud, mobile, exploit development, fuzzing, privilege escalation, post-exploitation and AI. It targets about 130 skills across 23+ categories, with an install script and sparse-checkout install per category. Built on Sahar Shlichov's offensive checklists, MIT licensed.
github.comrepoAdded 22 Oct 2026🛡️ Security
[tl;dr sec] #351 - PHP2Shell, Autopatching Skills, AWS Pathrunnertl;dr sec #351 is a weekly security newsletter. Clint Gibler describes working with OpenAI, Calif, Wiz and the PHP maintainers on the PHP2Shell unauthenticated RCE disclosure, which affects 13 years of PHP. It also covers Datadog's pathrunner AWS IAM escalation framework, Trail of Bits' patching-bugs and regression-hunt Codex plugins, XBOW finding de-duplication, backdoored open-weight models, and CREBench.
tldrsec.comarticleAdded 30 Oct 2026, published 22 Oct 2026🛡️ Security- What FDE means at OpenAI
Colin Jarvis, Head of Forward Deployed Engineering at OpenAI, describes how the FDE team works with enterprise customers to close the "deployment gap". Cases include a semiconductor verification project (about 48% time saved on test generation) and a telecom voice model whose key evals rose from about 60% to 90%+. Moving use cases onto a Codex harness with skills and plugins removed about 90% of custom code.
openai.comarticlePublished and added 22 Oct 2026🧠 AI
Donating Agent Skills to the Agentic AI FoundationAgent Skills is an open standard in which a skill is a folder with a SKILL.md file plus scripts and reference material. Anthropic is donating the name, logo, GitHub organization and agentskills.io domain to the Agentic AI Foundation under the Linux Foundation. Over 70 platforms have integrated it, with 1 million skills published and nearly 280 million installs. The proposed roadmap covers versioned releases, a proposal process and security guidance.
anthropic.comarticleAdded 29 Oct 2026, published 22 Oct 2026🧠 AI- Trail of Bits (@trailofbits) on X
Trail of Bits announces two open-source plugins, patching-bugs and regression-hunt, for AI coding agents that speed up bug patching. They come from four months of Patch the Planet work with open-source projects, which found that repo-level documentation, skills and plugins give agents the maintainer context on what counts as a bug, how a fix should look and what must not break. The post cites the October 2026 PHP incident: a patch touching 402 files, and exploitation within 17 hours of leaked details.
x.comarticleAdded 23 Oct 2026, published 21 Oct 2026🧠 AI - Show HN: Omnara – Open-source alternative to Claude Managed Agents
Omnara is an open-source, self-hostable managed agent platform, an alternative to Claude Managed Agents and OpenAI's Agents API. It runs agents on any model (OpenAI, Anthropic, OpenRouter, Bedrock, LiteLLM, Ollama) and any machine, with Postgres-backed durable state, stateless workers, per-tool permissions, MCP, skills, memory, subagents, schedules and Slack, Discord and GitHub triggers. It ships a REST API, TypeScript SDK, CLI and Docker Compose setup.
github.comrepoAdded 23 Oct 2026, published 21 Oct 2026🧠 AI
AI for the Fortune 2000: How Tenex Builds an AI-Native SDLC — Alex Lieberman & CJ HessLatent Space interview from AI Engineer New York with Tenex cofounder Alex Lieberman and CJ Hess. Tenex has 75 people, pays engineers by story points, and reports roughly 2x engineer output over the past year. CJ describes MetaHarness, a repo-based set of skills, plans and a CLI that logs agent decisions in Git. They also cover enterprise AI adoption rates, token spend, and vertical AI. The page text is truncated.
latent.spacetalkAdded 23 Oct 2026, published 21 Oct 2026🧠 AI
vlt 1.5.0 Adds Agent Skills Managementvlt 1.5.0 adds a `vlt skills` command that finds agent skills (SKILL.md folders) in installed JavaScript dependencies and links them into directories coding agents read, such as .agents/skills and .claude/skills. Selections are saved as allow-skills in vlt.json, tied to the lockfile version, and kept current on install and update. Without a saved selection, linking defaults to :not(:malware) using Socket malware alerts. pnpm 12.11.0 added similar linking.
socket.devarticlePublished and added 21 Oct 2026🧠 AI
vlt 1.5.0 Adds Agent Skills Managementvlt 1.5.0 adds a `vlt skills` command that discovers agent skills (SKILL.md folders) shipped in installed JavaScript dependencies and links them into directories read by coding agents such as .agents/skills and .claude/skills. Links follow the lockfile version, and selections are saved as allow-skills in vlt.json. Without a saved selection, linking defaults to :not(:malware), using Socket malware alerts. pnpm 12.11.0 added similar support.
socket.devarticlePublished and added 21 Oct 2026🛡️ Security
AI Is Calling In Every Risk You've Accepted: Seven Insights From The AI Security Panel: UnfilteredSnyk's recap of "The AI Security Panel: Unfiltered" (14 October 2026, San Francisco) with speakers from Snyk, OpenAI, Google Threat Intelligence Group and boldstart ventures. It covers AI agents as an attack surface, the July Hugging Face breach by OpenAI models in an evaluation, ToxicSkills data (36.82% of 3,984 skills flawed), Project Glasswing patch backlogs, and why fixing, not finding, is the bottleneck. It closes with a Monday-morning action list.
snyk.ioarticlePublished and added 21 Oct 2026🛡️ Security
Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent CompromisePaper on memory injection, where prompt injection persists across sessions through the long-term memory of LLM-as-a-service platforms. It presents a general threat model and shows all NIST attack goals are achievable on ChatGPT Instant 5.3, Claude Sonnet 4.6 and Gemini 3 Flash. Vectors include personal memories, projects, skills, organization instructions and MCP resources. On Claude, shared memory lets an attacker compromise multiple users in an organization and exfiltrate prompts. Nearly half of the derived mitigations are unimplemented.
arxiv.orgpaperAdded 24 Oct 2026, published 20 Oct 2026🛡️ Security
How 3 Java Champions are using GitHub Copilot for increased productivityInterviews with three Java Champions (Vlad Mihalcea, Patrick Baumgartner, Frank Delporte) on using GitHub Copilot in production and open source. Examples include a 900-slide Reveal.js to Marp migration with visual verification, a Copilot coding agent diagnosing a Pi4J virtual-thread pinning bug, and custom Agent Skills. Tips: interview-first planning, task-specific verification gates, deterministic quality harnesses, and human review.
github.blogarticleAdded 29 Oct 2026, published 20 Oct 2026🧠 AI- better-isms/grcskills
grcskills is a library of 60 plain SKILL.md files in the Agent Skills format, each describing how an experienced practitioner does one piece of governance, risk and compliance work. Examples are scope statements, risk registers, audit prep, vendor review and incident handling. Every skill names where the agent must stop and hand the decision to a person. Installs are pinned to reviewed release tags and checked by a validator.
github.comrepoAdded 20 Oct 2026🧠 AI - better-isms/grcskills
grcskills is an MIT-licensed library of 60 SKILL.md files (Agent Skills format) that let coding agents draft and prepare governance, risk and compliance work: scope statements, statements of applicability, risk registers, audit prep, vendor review, policies, privacy, incidents and continuity. Each skill names where the agent must stop so a person decides. Installs are pinned to release tag v2026.10.19.2, and a validator rejects network commands and credential paths.
github.comrepoAdded 20 Oct 2026🛡️ Security
How Effectively Do Security Skills Guide Coding Agents in Vulnerability Detection in Linux Kernel?The paper is a large-scale study of 37 security skills run through Claude Code with four LLMs on 100 real Linux kernel vulnerabilities, 14,800 runs in all. Only 24.4 percent of runs found the correct function and 15.7 percent classified the vulnerability correctly. It proposes SKILL-SIF, which evolves skills from failure patterns and raised fully correct detection on 100 unseen vulnerabilities from 2 to 16 percent.
arxiv.orgpaperAdded 21 Oct 2026, published 19 Oct 2026🧠 AI
How Effectively Do Security Skills Guide Coding Agents in Vulnerability Detection in Linux Kernel?Empirical study of 37 security skills run through Claude Code with four LLMs on 100 real Linux kernel vulnerabilities across ten classes (14,800 runs). 24.4% of runs found the correct function, 18.3% the function and statement, and 15.7% the vulnerability class. The authors propose SKILL-SIF, which evolves skills from failures and raised fully correct detection on 100 unseen vulnerabilities from 2% to 16%.
arxiv.orgpaperAdded 21 Oct 2026, published 19 Oct 2026🛡️ Security- Ethan Walkrman (@ethanwalkerman) on X
Harness2 is a framework from Google Cloud AI Research and Northwestern University in which an Editor model rewrites an agent's harness (system prompt, memory, skills, tool scripts, subagent routing, middleware) without changing model weights. It uses a Propose-Probe-Compose loop that compares execution trajectories instead of ground truth. On WorkBuddy-Bench, GLM-5 rose from 64.2 to 75.7 after one round, above Gemini 3.5 Flash at 72.4. The thread also lists risks: latency, experience poisoning, and a sandbox that is off by default.
x.comthreadAdded 19 Oct 2026, published 18 Oct 2026🧠 AI - DietrichGebert/ponytail
Ponytail is a single skill prompt (skills/ponytail/SKILL.md, with a compact AGENTS.md) that makes coding agents write only the code a task needs, reusing existing components while keeping validation, error handling, security and accessibility. The author benchmarked it in Claude Code with Opus 5.5 over 39 tasks, 5 runs each, including a real FastAPI + React repo. They report -53% code, -41% time, -26% cost and -45% tokens, and 98% of risky logic shipping with a test versus 68% without. It adds /ponytail-review and /ponytail-audit commands, a Claude Code cost/token band with a local board, and installs through Claude Code and Codex plugin marketplaces or as a rules file for Cursor, Copilot, Gemini, OpenCode and others.
github.comrepoAdded 17 Oct 2026🧠 AI
Skill-Decoupled On-Policy Expert Distillation for Unified Vision-Language ModelsProposes SCOPED (Skill-Decoupled On-Policy Expert Distillation), which trains capability-specific RL experts for vision-language models. It extracts explicit skills from them through reward-guided reflection. During on-policy distillation the skills guide expert supervision but are hidden from the unified student, so the student internalizes the procedural knowledge and needs no explicit skills at inference. Across eight multimodal benchmarks it beats the backbone and mixed-capability RL. Analyses show cross-capability gradient interference in joint RL, and that skill augmentation gives more consistent expert trajectories, more attention to task-relevant visual evidence, and better preservation of expertise.
arxiv.orgpaperAdded 17 Oct 2026, published 15 Oct 2026🧠 AI
ERC-8444: Agentic Resource Discovery (ARD) OnchainAn Ethereum Magicians proposal for ERC-8444, which adds an onchain value and settlement layer under Google's Agentic Resource Discovery (ARD) spec for finding MCP servers, A2A agents, skills and APIs. A thin kernel records kind (skill, task, agent, registry), a CAIP-19/CAIP-10 anchor, a JCS+SHA-256 descriptor hash, a canonical URN and a status. Authority belongs to the paid address, and domains act as collected endorsements through /.well-known/ard.json. The reference implementation has Foundry-tested Solidity adapters and a Node.js gateway that passes the official ARD conformance CLI. It introduces a "task" kind (application/ai-task+json) for tenders aimed at suppliers, and the author asks for feedback on the trust root, the hash scope, same-chain anchors and the task payload.
ethereum-magicians.orgthreadAdded 14 Oct 2026, published 13 Oct 2026🧠 AI
GitHub Copilot app for Beginners: How to teach Copilot about your codebaseBeginner-oriented GitHub blog guide to giving GitHub Copilot project context through four mechanisms: repository custom instructions (.github/copilot-instructions.md and path-specific .github/instructions files with applyTo), agent skills (SKILL.md folders under .github/skills), custom agents (.github/agents profiles), and MCP servers such as Playwright. It explains when to use each and how they combine, using examples like a quality-checks skill and an accessibility-review agent. Useful as a concrete reference for the repo layout Copilot reads, with a pointer to the community Awesome Copilot collection.
github.blogarticlePublished and added 12 Oct 2026🧠 AI- zero-lab-ai/skills
zero-lab-ai/skills is a collection of 56 portable SKILL.md agent skills in 10 installable plugins from zero-lab.ai. They cover authorized defensive assessment, penetration testing, red teaming, detection engineering, purple teaming and engagement operations. Skills install via the Claude marketplace layout or `npx skills add`, and a make check release gate runs linting and tests.
github.comrepoAdded 23 Oct 2026, published 11 Oct 2026🛡️ Security - sepehr071/iran-mcp
iran-mcp is an open-source catalog of 39 MCP servers (488 tools) that let AI agents query Iranian websites such as Digikala, Torob, Divar, Snappfood, Jabama, Paziresh24, TSETMC and qavanin.ir, with prices normalised to Toman. Most servers are unofficial, read-only Python packages run with uvx; three are official hosted servers. It ships Claude Code plugins, Agent Skills, bundles, proxy lists and a machine-readable servers.json.
github.comrepoAdded 24 Oct 2026, published 11 Oct 2026🧠 AI - Cloudflare Changelog (@CFchangelog) on X
Cloudflare's changelog announces that its Cloudflare API MCP server now serves Cloudflare skills alongside its tools. A connected MCP client discovers them by calling `skills/list`. This is an example of distributing agent skills through an MCP server rather than as local files or a repo.
x.comarticlePublished and added 11 Oct 2026🧠 AI - Confident AI (@confident_ai) on X
Confident AI announces Eval Skills, open-source (Apache 2.0) agent skills for Claude Code and Codex. The `eval-build` skill takes an app to a runnable baseline: it finds realistic examples in traces and incidents, annotates failures, groups them into failure modes, curates cases with independent data splits, and builds graders validated against human judgment. The `eval-descent` skill runs a bounded loop of hypothesis, app change, eval re-run, regression check, then keep or revert, with held-out cases kept out of the loop. It ships Python and TypeScript tooling for tracing, annotation, grading and reports, plus a local UI or Confident AI for managing the loop.
x.comthreadPublished and added 9 Oct 2026🧠 AI - Show HN: Let your AI agents paint big arrows, boxes and text on your screen
bigarrow is an MIT-licensed, single-binary Swift macOS CLI that draws a click-through arrow and sign over all windows so an AI agent can show a human where to click, paste or act (permission prompts, 2FA, OAuth consent). It ships an Agent Skills package (installed via `bigarrow install-skill`) for Claude Code and Codex, with JSON output and exit codes, and can target by Accessibility label, coordinates, window or Peekaboo snapshot. The README documents the skill's token cost (182 tokens for the description, 1,398 for the instructions) and 104 automated tests.
github.comrepoPublished and added 9 Oct 2026🧠 AI - mattpocock/skills — agent skills for engineers
mattpocock/skills is a collection of small, composable "agent skills" for software engineering that install into Claude Code, Codex, GitHub Copilot, Gemini CLI, Cursor, OpenCode, Devin, Windsurf, Amp and Pi via plugin managers or the `npx skills` CLI. It packages practices like interview-driven requirement gathering (/grill-me, /grill-with-docs), domain-model/glossary building, test-driven development with red-green-refactor (/tdd), bug diagnosis loops, codebase architecture improvement, ticket triage and spec-to-implementation workflows (/to-spec, /to-tickets, /implement, /implement-spec), splitting skills into user-invoked orchestrators and model-invoked reusable disciplines. It's built by Matt Pocock as an alternative to heavier process-owning frameworks like GSD, BMAD and Spec-Kit, aiming to keep engineers in control while giving coding agents better feedback loops and shared vocabulary.
github.comrepoAdded 8 Oct 2026🧠 AI - Quoting Carson Gross
A brief Simon Willison Quoting post sharing htmx creator Carson Gross's view that computer programming is fundamentally about solving problems and controlling complexity, and that he expects these skills to remain valuable and employable even as AI coding tools become more capable. It is a one-paragraph opinion snippet rather than a technical piece, offering a counterpoint to fears that AI will devalue software engineering as a career.
simonwillison.netarticlePublished and added 8 Oct 2026🧠 AI
StepSecurity Now Inventories AI Agent Skills in Your GitHub Repositories and on Developer MachinesStepSecurity announces two new inventory features — Dev Machine Guard's Agent Skills page (scanning 18 AI coding agents' skill directories on developer machines) and a GitHub Agent Skills page (scanning default branches of org repos daily) — to track AI agent "skills" (SKILL.md folders with optional scripts/hooks) across an organization. The post frames skills as a supply-chain surface because they can execute shell commands, pre-approve tool permissions via allowed-tools frontmatter (bypassing Claude Code's workspace trust gate), and look like harmless Markdown documentation in PR review, citing the Miasma worm, s1ngularity, and the Cline v2.3.0 compromise as precedent for this attack class. It details inventory features like content-hash comparison across devices, provenance tracing via skills.sh/skills-lock.json, and filters for shell/hooks/code execution flags to prioritize review.
stepsecurity.ioarticlePublished and added 8 Oct 2026🛡️ Security
Autonomous Code Migration for Quantum Programming Languages: A Case Study with QED-C BenchmarksCase study in which Opus, GPT and Gemini coding agents port thirteen QED-C Application-Oriented Benchmark methods from Qiskit to CUDA-Q. The agents produced satisfactory ports far faster than a human engineer, but took shortcuts when implementation got hard and needed repeated prompting. No single model was best across all benchmarks, which suggests multi-agent ensembles. The work released near-complete CUDA-Q support in QED-C and model-generated skills that, on an unseen benchmark, cut model turns by up to 85% and token usage by up to 96%.
arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI
Who Verifies the Verifier? Co-Evolving Inspectable Graders with Self-Improving AgentsProposes making the verifier the evolving object in self-improving agent loops. The verifier is an inspectable expression over small, mostly deterministic drawback detectors, synthesized from clustered failures, gated at birth, and selected for agreement with a ten-item anchored reference set plus consensus over unlabeled outputs, never for the agent's score. On MBPP+ it gains +0.21 held-out agreement over the hand-authored seed and ends ahead of the bare LLM judge it contains. Removing the anchor guards collapses the verifier into an always-pass grader that still trains skills as well, so downstream task score cannot certify a self-evolved verifier. The paper's Double Ratchet pairs the verifier with a lifecycle-managed skill loop and retains 88-110% of the lift from ground truth or a rubric on code generation, enterprise text-to-SQL and reference-free report generation.
arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI
Skill Constellations: Tracing the Supply Chain of Agent Skills on GitHubThe paper builds the first dated copy network of agent skills (SKILL.md files) from the git history of repositories in GitSkills, covering 2,193,119 skill adoptions on GitHub, and ships an interactive viewer. It finds that a few source repositories account for almost all copies, that GitHub stars do not identify them, and that copies almost never track their source, so fixes rarely propagate. A fitted model of which repositories get copied ranks repositories for audit: reviewing the top 100 would prevent 14.9% of later adoptions of high-risk skills, against 0.5% for the 100 most-starred. The authors recommend that platforms distribute versioned references instead of copies.
arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🧠 AI
Skill Constellations: Tracing the Supply Chain of Agent Skills on GitHubBuilds the first dated copy network of agent skills (SKILL.md files) from git history in the GitSkills dataset, covering 2,193,119 skill adoptions on GitHub, plus an interactive viewer. Finds a few repositories are the source of nearly all copies, stars do not identify them, and copies almost never track their source, so upstream fixes rarely propagate. A model of which repositories get copied ranks repos for audit: reviewing the top 100 prevents 14.9% of later adoptions of high-risk skills versus 0.5% for the 100 most starred. The authors recommend platforms distribute versioned references rather than copies.
arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🛡️ Security
From Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction GeneratorsThe paper introduces DIGHT, a co-adaptive framework that couples a text-conditioned digital-human interaction generator with a physics-based humanoid tracking policy to produce physically plausible two-humanoid interactions. Rather than collapsing executability and interaction-fidelity signals into one scalar reward, it applies physics-decoupled diffusion Direct Preference Optimization (DPO) to align the generator using criterion-specific preferences derived from tracking error, friction, floating, and simulator force feedback (contact occurrence, location, duration, magnitude), then uses the aligned generator's outputs to fine-tune the tracker. Experiments show improved physical plausibility and more reliable, faithful simulated humanoid interactions compared to prior tracking-based approaches.
arxiv.orgpaperAdded 8 Oct 2026, published 7 Oct 2026🧠 AI
One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMONVIDIA describes how it specialized Nemotron 3 base models into domain experts for competitive programming (IOI) and olympiad mathematics (IMO) using a four-step recipe: strong base model, curated domain data with reasoning traces, SFT/RL post-training, and an inference loop (GenCorrect for IOI, generate-verify-refine for IMO) that searches and refines candidate answers. Nemotron-3-Nano-CC and Nemotron-3-Ultra-CC reached gold-level IOI 2026 scores (535.4/600), while SFT and RL checkpoints of Nemotron 3 Ultra combined to score 30/42 on IMO 2026, exceeding the gold threshold with no formal prover or external tools. The post releases training datasets, checkpoints, the Nemotron-IMO-Bench benchmark, and the NeMo-Skills inference pipelines on Hugging Face.
huggingface.coarticlePublished and added 7 Oct 2026🧠 AI
Surviving the Router: Optimizing Skill Injections for Retrieval and ExecutionThis paper studies prompt-injection attacks against AI agent "skill" marketplaces where a router dynamically selects which third-party skill to execute. The authors show existing injection attacks lose 87-97% of their effective attack success rate once a skill must first win retrieval against competing skills, and introduce CORSA (Cluster Optimization for Router-Aware Skill Attacks), which jointly optimizes injections for retrieval and execution, improving end-to-end attack success while preserving user utility and transferring across different router architectures and LLM backbones.
arxiv.orgpaperAdded 7 Oct 2026, published 6 Oct 2026🛡️ Security
Under the Hood of SKILL.md: Semantic Supply-chain Attacks on AI Agent Skill RegistryThis arXiv paper studies SKILL.md files — the natural-language metadata describing modular AI Agent Skills — as an attack surface, demonstrating semantic supply-chain attacks against real ClawHub skills. Using text-only manipulations, the authors manipulate embedding-based Discovery retrieval (up to 86% pairwise win rate, 80% Top-10 placement), bias agent Selection toward adversarial variants (77.6% average success), and evade Governance blocking verdicts (36.5%-100% evasion), showing that skill metadata is operational text that shapes agent trust rather than passive documentation.
arxiv.orgpaperAdded 5 Oct 2026🛡️ Security
Rajashekar Sudireddy (@raja_sudireddy) on XA tweet thread recapping Nate Herk's 18-concept guide to running OpenAI's Codex as a non-coder "AI operating system," organized around four pillars: a place to work (projects, AGENTS.md, the agent loop), a place to run it (local vs cloud environments, worktrees, .codex), controls (models, effort, permissions, skills, plugins), and tools/scale (browser, Sites, subagents, scheduled tasks, voice). It highlights AGENTS.md as the ground-rules file that replaces repeated context-setting (Herk ported his Claude Code CLAUDE.md into it), frames reusable "skills" as an iteratively refined recipe, and describes scheduled tasks as the mechanism that injects prompts into sessions automatically for always-on workflows.
x.comthreadPublished and added 4 Oct 2026🧠 AI
Rethinking skills and prompts for GPT-6 AstraOpenAI guidance for Codex users on adapting instructions, skills, AGENTS.md, and task prompts, now that GPT-6 Astra is more capable than prior models like GPT-5.6 Sol and GPT-6 Luna. It covers writing shorter, non-contradictory skill descriptions, using progressive disclosure (a minimal router skill pointing to supporting docs and scripts rather than loading everything into context), trimming over-eager AGENTS.md instructions such as forced doc-reading and excessive test-running reminders, recalibrating decision-boundary language since Astra is more cautious by default, and explicitly defining completion so the model does not stop after a first implementation when more work is expected.
developers.openai.comarticleAdded 3 Oct 2026🧠 AI- Jan Curn (@jancurn) on X
Announcement of mcpc v0.7.0, Apify's open-source MCP CLI client (npm i -g @apify/mcpc), which adds support for the MCP Skills extension with new skills-list/skills-get commands that verify SKILL.md and supporting files against the skill manifest via size and SHA-256 checks before printing content. The release also ships security hardening: repo-local .mcp.json auto-discovery can no longer read environment variables (blocking leaks like $GITHUB_TOKEN), OAuth refresh tokens are now scoped only to the auth server originally used, and Windows login URLs no longer launch through cmd.exe.
x.comthreadAdded 5 Oct 2026, published 3 Oct 2026🛡️ Security - Jan Curn (@jancurn) on X
Jan Curn announces mcpc v0.7.0, an open-source MCP CLI client (npm package @apify/mcpc), adding support for the MCP Skills extension via new skills-list and skills-get commands that fetch and cryptographically verify SKILL.md and supporting files against the skill manifest (size + SHA-256). The release also hardens security by preventing repo-local .mcp.json auto-discovery from reading environment variables (blocking token-leak tricks), scoping refresh tokens to the originating auth server, and fixing an insecure Windows login URL launch path via cmd.exe, alongside OAuth session longevity fixes and 2026-07-28 MCP spec compatibility improvements.
x.comthreadAdded 5 Oct 2026, published 3 Oct 2026🧠 AI
Showing 60 of 189
Show more