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Contexory
Author agent skills with your team, sync to any AI agent
Where teams author, review & version AI agent skills — then get them into every agent. Non-devs write them (no YAML); you keep git + review. Auto-syncs to Claude Code & OpenClaw; two-way GitHub sync feeds your own agents (LangGraph, custom). Portable markdown, no lock-in.
Agent skills are the instructions that make an agent good at your work — and they're usually a mess: scattered SKILL.md files or repo configs, no version history, no review, copy-pasted between machines and teammates. The deeper problem: the person who should write a skill is whoever knows the workflow — ops, support, research — not whoever knows YAML. So they don't, and the skill ends up a developer's secondhand guess.
Contexory fixes both. Non-devs author in a real collaborative editor (an AI assistant handles the frontmatter/structure); you get versions + review/approval like code.
Then it gets the skill into your agent, two ways: • Claude Code & OpenClaw — published skills auto-sync via our plugins (on npm + ClawHub + the Claude Code marketplace). • Your own agent (LangGraph, CrewAI, custom) — two-way GitHub sync keeps skills as portable markdown checked into your repo, so your agent loads them the way it already does. No lock-in.
It's early and I'd genuinely love your hardest questions and "why not just a repo + PRs?" challenges (I think the non-dev authoring + review layer is the point — happy to argue it).
About Contexory on Product Hunt
“Author agent skills with your team, sync to any AI agent”
Contexory was submitted on Product Hunt and earned 0 upvotes and 3 comments, placing #12 on the daily leaderboard. Where teams author, review & version AI agent skills — then get them into every agent. Non-devs write them (no YAML); you keep git + review. Auto-syncs to Claude Code & OpenClaw; two-way GitHub sync feeds your own agents (LangGraph, custom). Portable markdown, no lock-in.
On the analytics side, Contexory competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how Contexory performed against the three products that launched closest to it on the same day.
Who hunted Contexory?
Contexory was hunted by Contexory. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Contexory including community comment highlights and product details, visit the product overview.
Hi PH 👋 I'm Desmond from Contexory.
Agent skills are the instructions that make an agent good at your work — and they're usually a mess: scattered SKILL.md files or repo configs, no version history, no review, copy-pasted between machines and teammates. The deeper problem: the person who should write a skill is whoever knows the workflow — ops, support, research — not whoever knows YAML. So they don't, and the skill ends up a developer's secondhand guess.
Contexory fixes both. Non-devs author in a real collaborative editor (an AI assistant handles the frontmatter/structure); you get versions + review/approval like code.
Then it gets the skill into your agent, two ways: • Claude Code & OpenClaw — published skills auto-sync via our plugins (on npm + ClawHub + the Claude Code marketplace). • Your own agent (LangGraph, CrewAI, custom) — two-way GitHub sync keeps skills as portable markdown checked into your repo, so your agent loads them the way it already does. No lock-in.
It's early and I'd genuinely love your hardest questions and "why not just a repo + PRs?" challenges (I think the non-dev authoring + review layer is the point — happy to argue it).