Ponytail provides guidance for AI agents to reduce unnecessary coding work.
Honey
Honey reduces token usage by giving AI coding agents a cross-tool skill for writing less code and prose.

About Honey
Honey is an open source, cross-tool skill for AI coding agents intended to reduce token usage and LLM API costs. It encourages less code through a YAGNI-first approach, less prose by answering directly, and denser agent-to-agent handoffs using compact JSON or ESON. It uses an always-on core with on-demand satellites and selects lite, full, or ultra intensity based on the request.
It is listed as working with Claude, Claude Code, Cursor, GitHub Copilot, Codex, Gemini CLI, Windsurf, Cline, OpenClaw, oh-my-pi, Kiro, Kilo Code, and Hermes Agent. Specified safety-related code, including validation, error handling, auth, secrets, migrations, deletes, and explicitly requested items, is left uncompressed, and the compact handoff format is for agent-to-agent use, not user-facing answers. The repository includes a benchmark directory for reproducing comparisons.
Key features
- Writes less code using a YAGNI-first existence-to-minimum ladder
- Shortens prose by answering first and omitting narration
- Formats agent-to-agent handoffs as compact JSON or ESON
- Chooses lite, full, or ultra intensity based on request
- Excludes validation, auth, secrets, migrations, and deletes from compression
- Offers core skill plus review, eco, gain, and compress satellites
- Available as an open source repository
- Listed as working with multiple coding agents including Claude Code, Cursor, Copilot, Codex, and Gemini CLI
- Includes a reproducible benchmark directory with documented methodology
Honey at a glance
- Category
- AI & Machine Learning › AI Coding Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Honey FAQ
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