Skills SDK for Codex/AI coding agents: author, validate, evaluate, and sync runtime projections through ask.
This repository also configures its own agents. See what Agent-Skills tells them →
Skill Codex
Explains, summarizes, and turns Matthias Luebken's talk on embedding Pi-style coding agents into safe product-design artifacts: tool-contract sketches, guardrail checklists, session-record models, and malleable-software review plans. Use when the user asks about OpenClaw, Pi-style product agents, lifecycle guardrails…
Skill Codex
Provides detailed answers, conceptual explanations, workflow guidance, and framework-based analysis about Edouard Maleix's talk "How AI-First Dev Teams Build Collective Intelligence — One Attributed Mistake at a Time." Use when the user asks about giving coding agents their own identity and signed commits, the…
Skill Codex
Summarizes Simon Maple's AI Native DevCon welcome and explains the conference framing: context window, latent space, tool pool, hallway track, attendee goals, and practical learning themes. Use when the user asks about the event opening, conference themes, AI-native development framing, or how to orient work around…
Skill Codex
Use when the user asks about Luke Marsden's talk "Giving Every Agent Its Own Desktop: Lessons from Dogfooding HelixML" — including questions about HelixML, giving each agent its own GPU-accelerated desktop, spec-driven development with plan/implement phases, scaling agents by task vs by org-shape, centralized vs…
Skill Codex
Answers questions about, summarises key insights from, and helps apply concepts from Simon Martinelli's talk "Lessons from Spec-driven Development" — providing verbatim-grounded explanations, audits, and artifact drafts. Use when the user asks about the AI Unified Process, system use cases as specs (vs user stories)…
Skill Codex
Explains James Moss's team-skills workflow and helps design skill governance: decomposition, ownership, versioning, eval scenarios, quality review, and lifecycle maintenance. Use when the user asks about moving from solo skill hacks to team workflow, avoiding skill sprawl, or treating skills like software.
Skill Codex
Use when the user asks about Simon Obstbaum and Rob Willoughby's AI Native DevCon talk on measuring AI agents, output evals versus trajectory evals, instrumentation, compliance, and skill activation metrics.
Skill Codex
Explains Robert Overweg's One Brain, No Filtering talk and helps design safe knowledge-memory systems: context maps, retrieval rules, provenance labels, local knowledge-store structure, and review checkpoints. Use when the user asks about agent memory, unified knowledge bases, reducing context loss, or designing…
Skill Codex
Assists with questions about Guy Podjarny's talk "Skills are the new Code". Use when the user wants to understand, apply, audit, or explore frameworks from this keynote — including the five engineering disciplines for skills (static analysis, evals, security testing, dependency management, observability), the three…
Skill Codex
Use when the user asks about Katie Roberts''s talk "Stop Maintaining, Start Evolving: Applying AI-Native Practices to Brownfield Codebases" — including questions about using AI to build large complex systems (her 350k-line Rust S3 clone experiment), test oracles, flaky tests with AI agents, why 100% test coverage is…
Skill Codex
Use when the user asks about Katie Roberts's talk "Stop Maintaining, Start Evolving: Applying AI-Native Engineering in Brownfield Codebases" (AI Native DevCon, June 2026) — including questions about brownfield vs greenfield AI engineering, the three methodologies (pseudo-greenfield, strangler fig pattern, branch by…
Skill Codex
Use when the user asks about Steve Ruiz's AI Native DevCon talk on tldraw, Make Real, annotations as prompt input, canvas workflows, tldraw computer, and agents collaborating on an infinite canvas.
Skill Codex
Use when the user asks about Lieven Scheire's talk "Artificial Intelligence" (a Belgian physicist/comedian's keynote on AI for a developer audience) — including questions about his one-sentence definition of AI as "a new kind of software good at pattern recognition", the history of AI from the 1956 Dartmouth workshop…
Skill Codex
Explains Oleg Selajev's Docker Sandboxes talk and helps design safe, conceptual agent-isolation policies: file-sharing boundaries, network policy, secret isolation, audit expectations, and team rollout questions. Use when the user asks about sandboxed agents, hard isolation, local agent risk, or how to reason about…
Skill Codex
Summarizes Rob Sloan's harness-engineering talk and creates safe design artifacts for agent context beyond code: product-intent packets, design constraints, acceptance criteria, context ownership, and review gates. Use when the user asks about making non-code context agent-ready or improving AI work with…
Skill Codex
Use when the user asks about Shaun Smith's AI Native DevCon talk on MCP transports, remote Streamable HTTP servers, stateless protocol direction, Hugging Face MCP adoption, and future context transports.
Skill Codex
Explains Paul Stack's architecture-first AI workflow and helps create safe design artifacts: intent documents, architecture constraints, planner/reviewer loops, UAT criteria, and agent-output review gates. Use when the user asks about humans owning architecture while agents implement, why vibes do not scale, or…
Skill Codex
Explains the Product Brain talk and helps design curated product-memory systems for AI-assisted product work: knowledge structure, provenance, synthesis cadence, ownership, and agent-ready context packets. Use when the user asks about product context for AI, product knowledge management, product documentation for…
Skill Codex
Use when the user asks about Don Syme's AI Native DevCon talk on Continuous AI, GitHub agentic workflows, repository automation, and safe developer-controlled automation loops.
Skill Codex
Defensive review of AI-agent skills, plugins, and tools using Liran Tal's security principles. Use when assessing provenance, permissions, data exposure, sandboxing, or approval boundaries before adoption.
Skill Codex
Use when the user asks about Ian Thomas's talk "AI Native Engineering" (Meta / Reality Labs / Horizon Experiences) — including questions about Meta's AI4P (AI For Productivity) programme, the 6-dimension / 5-level AI maturity model and self-assessment workshop, how Horizon rolled out AI tooling across 500+ engineers…
Skill Codex
Summarizes, explains, and applies Lars Trieloff's AI Native DevCon talk on browser-native agents. Use for browser agents, running AI in the browser, browser-as-runtime architecture, agent containment, local-versus-cloud tradeoffs, safe AI product integration, documented APIs, user consent, credential isolation, and…
Skill Codex
Answers questions about, summarizes, and applies May Walter's AI Native DevCon talk "From Blind Spots to Merged PRs" on runtime intelligence for coding agents. Use when the user asks about production telemetry for agents, prod-to-code mapping, performance fixes from runtime data, why automated PRs need provenance…
Skill Codex
Use when the user asks about Peter Wilson and Davide Eynard's AI Native DevCon talk on cq, a Stack Overflow-like knowledge commons for agents, local/team/public knowledge sharing, and lessons from Mozilla.ai.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: