The problem
AI agents re-reason through every task from scratch, even ones they’ve solved before:- Inconsistency: Agents take different paths or skip steps between runs — there’s no way to verify without watching
- Cost: Each reasoning pass costs tokens — the same tokens, for the same logic, every time
- Context bloat: Loading tool schemas (especially MCP servers) consumes tokens before any work begins
How pflow helps
pflow separates workflow authoring from execution:- Your agent designs the workflow once - figures out what nodes to use and how to connect them
- pflow compiles the workflow - saves it as a reusable
.pflow.mdfile - Execution is instant - run the same workflow with different inputs, zero reasoning cost
Built for agents
The workflow format is markdown — headings, YAML, and code blocks. Agents already think in this structure, so they can write and iterate on workflows using patterns they already know. A side effect: open a.pflow.md file on GitHub and it reads like documentation. Render it in your IDE and it’s self-explanatory. The same file that executes as a workflow also serves as its own docs.
From idea to command
Get started
Quickstart
Install pflow and connect your AI tool
Integrations
Set up Claude Code, Cursor, VS Code, and more
Adding MCP servers
Expand pflow with external tools
CLI reference
All commands documented

