The Problem

AI agents default to writing code. Ask for a date picker and the agent installs a library, writes a wrapper, adds styles, and discusses timezones. The result is bloated, slow, and expensive. Ponytail exists to stop that: it forces the agent to check whether a solution already exists before writing anything.

What This Does

Ponytail is a skill/plugin package that injects a decision ladder into agent behavior: skip if unneeded, use the stdlib, use native platform features, use installed dependencies, write one line, and only then write the minimum that works. The ruleset lives in skills/ponytail/SKILL.md and is injected via lifecycle hooks in hooks/.

The repo ships adapters for ten agent platforms (Claude Code, Codex, OpenCode, Pi, Cursor, Windsurf, and others), each with its own config file under .claude-plugin/, .codex-plugin/, .opencode/, and similar directories. A benchmarks/ folder contains a promptfoo config and results claiming 80-94% less code and 3-6x faster output across three models.

How It Is Wired

Execution starts at ponytailExtension in pi-extension/index.js:55, which registers commands and hooks. The core flow is simple: resolveSessionMode (line 17) reads the current mode, parsePonytailCommand (line 32) handles /ponytail commands, and setMode (line 59) writes the chosen mode to disk.

The critical path is short. ponytailExtension reaches getDefaultMode, which does a fs.readFileSync on the config file. setMode writes with fs.writeFileSync. That is the entire filesystem footprint: two files, two calls, no database, no network.

The most-connected module is hooks/ponytail-config.js — five files import it, and it owns normalizeMode, normalizeConfigMode, and normalizePersistedMode. The normalizePersistedMode function is called from six places, making it the highest-blast-radius change in the repo. The other hub is hooks/ponytail-instructions.js, which filters skill content by mode via filterSkillBodyForMode.

The .opencode/plugins/ponytail.mjs plugin reads and writes mode state and logs, while hooks/ponytail-runtime.js owns setMode and clearMode. The test harness in pi-extension/test/extension.test.js defines a fake sendUserMessage to simulate agent responses.

How To Use It

Install per platform. For Claude Code:

/plugin marketplace add DietrichGebert/ponytail
/plugin install ponytail@ponytail

For Pi:

pi install git:github.com/DietrichGebert/ponytail

For OpenCode, run from a checkout and add to opencode.json:

{ "plugin": ["./.opencode/plugins/ponytail.mjs"] }

No environment variables are required. The .env.example file exists but the hooks read config from the user's home directory, not from env vars. Active every session; /ponytail-review analyzes diffs for removable code, and /ponytail ultra maximizes the laziness level.

Real-World Use

A team maintaining a legacy API endpoint asks an agent to add email validation. Without Ponytail, the agent writes a regex, a validation utility, and tests. With Ponytail, the agent checks the platform: the browser has input type="email" or the language has a built-in validator, and writes nothing or one line. The examples/email-validation.md file demonstrates this exact pattern. The savings compound across a codebase with hundreds of small utility functions.

Code Health & Issues

Static analysis found 7 medium findings across 2 categories:

  • Medium - Empty catch blocks x3: hooks/ponytail-runtime.js, .opencode/plugins/ponytail.mjs, and tests/opencode-plugin.test.js contain catch {} blocks that silently discard errors. These should log or rethrow.
  • Medium - High branching density x4: hooks/ponytail-instructions.js, pi-extension/index.js, and .opencode/plugins/ponytail.mjs have 21 branch points over 73 lines in the worst case. The mode-normalization logic in hooks/ponytail-config.js is the main culprit.

SDLC gaps: no CI pipeline exists, no lockfile is committed (non-reproducible builds), and Dependabot/Renovate is not configured. The repo has tests and a license but no Dockerfile.

The Bottom Line

Ponytail is a well-scoped, genuinely useful tool for teams tired of fighting their agent's default verbosity. The multi-platform adapter approach is thoughtful, and the benchmarks are reproducible. The main risks are the silent error handling in the hooks and the missing CI/lockfile — fix those before relying on it in production. It is not a code-generation framework; it is a behavior modifier, and it does that job well.