ponytail Makes Your Agent Write Less Code, on Purpose
The fastest-growing agent repo on GitHub right now is a set of instructions telling your agent to do less. ponytail, gaining about 1,400 stars a day, injects one persona into Claude Code, Codex, Copilot CLI and about twenty other harnesses: the laziest senior dev, the one who says nothing and writes one line. Repo at https://github.com/DietrichGebert/ponytail.
The mechanism is a decision ladder that runs before any code gets written: does this need to exist at all, is it already in the codebase, is it in the stdlib, is it a native platform feature, is it in an installed dependency, is there a one-line solution β and only after six no's is the agent allowed to write the minimum necessary. Shipped as plugins, hooks and copy-paste rules across platforms. The reported numbers: about 54% fewer lines of code, 20% cheaper, 27% faster than baseline agents, with validation intact.
It's funny, but it lands on the sorest spot in agent economics right now. Models bill by the token and are trained to be thorough, which makes over-engineering the default failure mode β every unnecessary abstraction gets generated, reviewed, tested and maintained at your expense. A month ago the trending boards were full of skill collections teaching agents to do more things. The pendulum swinging to "teach it restraint" is the more interesting signal: the cheapest token is the one never generated, and the codebase your agent didn't bloat today is the context window it won't blow through next month.
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The mechanism is a decision ladder that runs before any code gets written: does this need to exist at all, is it already in the codebase, is it in the stdlib, is it a native platform feature, is it in an installed dependency, is there a one-line solution β and only after six no's is the agent allowed to write the minimum necessary. Shipped as plugins, hooks and copy-paste rules across platforms. The reported numbers: about 54% fewer lines of code, 20% cheaper, 27% faster than baseline agents, with validation intact.
It's funny, but it lands on the sorest spot in agent economics right now. Models bill by the token and are trained to be thorough, which makes over-engineering the default failure mode β every unnecessary abstraction gets generated, reviewed, tested and maintained at your expense. A month ago the trending boards were full of skill collections teaching agents to do more things. The pendulum swinging to "teach it restraint" is the more interesting signal: the cheapest token is the one never generated, and the codebase your agent didn't bloat today is the context window it won't blow through next month.
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