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Agent Playbooks
One instruction set for every AI coding agent
37 tested engineering playbooks — bug fixing, feature development, code review, security review, safe database migrations, incident response, and more — installed once, read natively by Claude Code, Cursor, GitHub Copilot, Codex, and 12 other AI coding tools. Every playbook has actually been run against a real test case before being published, not just written. Every release is Ed25519-signed and hash-verified before anything touches your project. Free, MIT-licensed, no account needed.
Hey PH — maker here. Built this because every AI coding tool wants
instructions in its own format, and an agent left to its own judgment
fails the same few ways every time: guessing at ambiguous requests
instead of asking, grading its own work instead of checking
independently, forgetting a project's conventions between sessions.
A couple of things I'd rather flag myself than have someone else find:
the installer isn't offline — it calls a small backend on every run to
fetch the current release — but every release is cryptographically
signed and hash-verified before anything touches your project, so a
compromised backend can't silently swap the content.
Happy to answer anything — what it doesn't cover, why one design choice
over another, etc.
About Agent Playbooks on Product Hunt
“One instruction set for every AI coding agent”
Agent Playbooks was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #151 on the daily leaderboard. 37 tested engineering playbooks — bug fixing, feature development, code review, security review, safe database migrations, incident response, and more — installed once, read natively by Claude Code, Cursor, GitHub Copilot, Codex, and 12 other AI coding tools. Every playbook has actually been run against a real test case before being published, not just written. Every release is Ed25519-signed and hash-verified before anything touches your project. Free, MIT-licensed, no account needed.
On the analytics side, Agent Playbooks competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Agent Playbooks performed against the three products that launched closest to it on the same day.
Who hunted Agent Playbooks?
Agent Playbooks was hunted by Chirag Mangal. 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 Agent Playbooks including community comment highlights and product details, visit the product overview.
Chirag Mangal