Core Ponytail Commands and Their Functions: The Complete CLI Reference

The six core Ponytail commands—/ponytail, /ponytail-review, /ponytail-audit, /ponytail-debt, /ponytail-gain, and /ponytail-help—enable developers to toggle AI intensity levels, audit over-engineered code, and track technical debt through declarative TOML definitions processed by the hooks/ponytail-runtime.js engine.

Ponytail is an open-source AI assistant developed in the DietrichGebert/ponytail repository that simulates a "lazy senior developer" to reduce code bloat. Instead of hard-coding logic for every operation, core Ponytail commands and their functions are defined as separate .toml configuration files, allowing the runtime to dynamically translate user intent into LLM prompts. This architectural choice keeps the command layer thin while delegating complex analysis to the underlying language model.

Architectural Overview: Declarative Commands and Runtime Execution

TOML-Based Command Definitions

Each command resides as a standalone configuration file under the commands/ directory. These files contain human-readable metadata (description) and the actual instructions (prompt) sent to the AI. For example, when you invoke /ponytail-review, the runtime loads [commands/ponytail-review.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-review.toml), extracts its prompt template, and forwards it to the LLM along with contextual data such as the current git diff.

The Runtime Engine (hooks/ponytail-runtime.js)

The [hooks/ponytail-runtime.js](https://github.com/DietrichGebert/ponytail/blob/main/hooks/ponytail-runtime.js) file serves as the orchestration bridge. It handles TOML parsing, environment variable injection, and LLM API communication. By separating command semantics (the "what") from execution logic (the "how"), Ponytail allows new commands to be added simply by dropping new .toml files into the commands/ folder without modifying JavaScript code.

Configuration Management (hooks/ponytail-config.js)

Default behavior is governed by [hooks/ponytail-config.js](https://github.com/DietrichGebert/ponytail/blob/main/hooks/ponytail-config.js), which reads the PONYTAIL_DEFAULT_MODE environment variable (accepting lite, full, ultra, or off) and locates user-specific override files. This ensures that intensity levels persist across sessions while remaining configurable per repository.

The Six Core Ponytail Commands Explained

/ponytail – Switching Intensity Modes

Source: [commands/ponytail.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail.toml)

This is the primary mode-switching command. It accepts one argument that determines how aggressively the AI applies the "lazy ladder" heuristic (YAGNI → stdlib → native → one-liner → minimum):

• lite – Conservative suggestions, minimal changes.
• full – Standard over-engineering detection (default if no argument provided).
• ultra – Aggressive deletion-first policy; prefers removing code over adding abstraction.
• off – Deactivates Ponytail, returning to normal development mode.

/ponytail-review – Over-Engineering Code Review

Source: [commands/ponytail-review.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-review.toml)

Use this command to analyze uncommitted changes or staged files. The LLM returns a list of one-line suggestions tagged according to the type of simplification required:

• delete – Remove unnecessary code entirely.
• stdlib – Replace custom logic with standard library equivalents.
• native – Use language-native features instead of polyfills or wrappers.
• yagni – Remove speculative functionality (You Aren't Gonna Need It).
• shrink – Compress verbose implementations.

Each suggestion may include a replacement code block that can be applied directly.

/ponytail-audit – Repository-Wide Over-Engineering Audit

Source: [commands/ponytail-audit.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-audit.toml)

While /ponytail-review focuses on active changes, the audit command scans the entire repository for systemic over-engineering patterns. It surfaces architectural debt such as excessive abstraction layers, redundant utility classes, and microservice granularity issues that violate the "lazy senior dev" philosophy.

/ponytail-debt – Harvesting Technical Debt

Source: [commands/ponytail-debt.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-debt.toml)

This command aggregates AI-generated comments (marked with delete, yagni, or other tags from previous reviews) into a structured debt ledger. This persistent record allows teams to schedule dedicated refactoring sprints to address earmarked removals without losing track of simplification opportunities discovered during daily development.

/ponytail-gain – Impact Scoreboard and Benchmarks

Source: [commands/ponytail-gain.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-gain.toml)

After applying Ponytail suggestions, use this command to visualize measurable improvements. The runtime queries benchmark medians to display:

• Lines of Code (LOC) reduction percentage.
• Execution speed improvements.
• Infrastructure cost savings (where applicable).

This read-only command provides the business justification for aggressive simplification by quantifying technical debt removal.

/ponytail-help – Quick Reference Card

Source: [commands/ponytail-help.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-help.toml)

The help command prints an inline cheat sheet listing all available intensity levels, recognized skill tags, and deactivation syntax (/ponytail off, stop ponytail, or normal mode). It is particularly useful for onboarding new team members or verifying the current mode setting without reading source documentation.

Practical Usage Examples

# Activate ultra-aggressive deletion mode

/ponytail ultra

# Review current branch changes for over-engineering

/ponytail-review

# Scan the entire repo for systemic complexity

/ponytail-audit

# Persist today's "delete" suggestions to the debt ledger

/ponytail-debt

# Show measurable impact from previous optimizations

/ponytail-gain

# Print quick-reference and current configuration

/ponytail-help

# Deactivate Ponytail for normal coding sessions

/ponytail off

Key Source Files and Implementation Details

File	Role
[commands/ponytail.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail.toml)	Intensity mode switching (lite, full, ultra, off).
[commands/ponytail-review.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-review.toml)	Prompt template for change-set over-engineering review.
[commands/ponytail-audit.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-audit.toml)	Prompt template for repository-wide architectural audits.
[commands/ponytail-debt.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-debt.toml)	Logic for harvesting tagged comments into the debt ledger.
[commands/ponytail-gain.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-gain.toml)	Prompt for generating benchmark-derived impact reports.
[commands/ponytail-help.toml](https://github.com/DietrichGebert/ponytail/blob/main/commands/ponytail-help.toml)	Quick-reference documentation prompt.
[hooks/ponytail-runtime.js](https://github.com/DietrichGebert/ponytail/blob/main/hooks/ponytail-runtime.js)	Core engine that loads TOML definitions and manages LLM communication.
[hooks/ponytail-config.js](https://github.com/DietrichGebert/ponytail/blob/main/hooks/ponytail-config.js)	Environment variable handling and default mode resolution.

Summary

• Six declarative commands control AI intensity and code analysis workflows in Ponytail.
• Command definitions reside in commands/*.toml files, making the system extensible without JavaScript changes.
• /ponytail switches between lite, full, and ultra modes; /ponytail-review and /ponytail-audit detect over-engineering at different scopes.
• /ponytail-debt tracks removal candidates in a persistent ledger, while /ponytail-gain quantifies optimization impact.
• Execution flow is handled by hooks/ponytail-runtime.js with configuration managed via hooks/ponytail-config.js and environment variables.

Frequently Asked Questions

What is the difference between /ponytail-review and /ponytail-audit?

/ponytail-review analyzes currently staged or unstaged code changes (the active diff), providing immediate feedback on over-engineering introduced in the current work session. /ponytail-audit performs a holistic scan of the entire repository, identifying systemic architectural issues and legacy complexity that exists outside of recent commits.

How does the runtime engine process TOML command definitions?

When a user invokes a command, hooks/ponytail-runtime.js reads the corresponding file from the commands/ directory, extracts the prompt field, and injects contextual data such as git state or file trees. The runtime then sends this composite prompt to the configured LLM API and parses the response to present tagged suggestions or execute state changes like mode switching.

Can I extend Ponytail with custom commands?

Yes. Because the command layer is declarative, you can create new functionality by adding a .toml file to the commands/ directory with description and prompt keys. The runtime automatically discovers and loads these files at startup, allowing you to define custom AI workflows (e.g., security reviews, documentation generation) without modifying the core JavaScript runtime.

Where is the technical debt ledger stored?

The debt ledger is generated and managed by the /ponytail-debt command as defined in commands/ponytail-debt.toml. While the exact persistence mechanism depends on the runtime implementation, the ledger typically writes to a project-local JSON or Markdown file (often .ponytail/debt.md or similar) that can be committed to version control or processed by CI pipelines to track refactoring progress.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}