What makes ponytail-review notable?

1.8K downloads. Trust evidence available

How should ponytail-review be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

ponytail-review

Quality review of a diff: bugs, security, real load, missing tests, speed, and what to delete. Each finding says what goes wrong and how to fix it. Skill: ponytail-review Owner: dietrichgebert Summary: Quality review of a diff: bugs, security, real load, missing tests, speed, and what to delete. Each finding says what goes wrong and how to fix it. Tags: latest:5.1.0 Version history: v5.1.0 | 2026-10-08T16:21:31.860Z | auto This release expands the skill from lean/over-engineering review to a full quality review including bugs, tests, security, scale, and perform

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.8k

Updated

Oct 10, 2026

Version

5.1.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.8K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.8K downloadsadoption · observed Oct 10, 2026
Latest release: 5.1.0release · observed Oct 8, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17beee6vfcnpy9kq5vh15rzzh88rnca:ponytail-review

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-dietrichgebert-ponytail-review/snapshot"

Documentation

CLAWHUB

48,258 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: ponytail-review
description: "Quality review of a diff: bugs, security, real load, missing tests, speed, and what to delete. Each finding says what goes wrong and how to fix it."
homepage: https://github.com/DietrichGebert/ponytail
license: MIT
---

Review a change like the senior developer who will be paged when it breaks.
Order of importance: correct, safe, holds under load, tested, fast, lean.
Lean still matters: every extra line must be read, tested and fixed later.
This is a report the user asked for, so give it in full.

## 1. Understand first

- Review what the user names: uncommitted or staged changes, a branch, a PR
  link, or files. Nothing named: the uncommitted changes, or the last commit
  if there are none.
- Read the diff, then the code it touches: callers of every changed function,
  the functions it calls, the tests, the README.
- Trace the real flow: where data comes in, what is stored, what goes out.
- A change can break code it does not touch. When a signature, return value
  or behavior changes, grep every caller.
- Find the expected load in the repo (README, deploy config): one person
  running a script, or many users and processes at once. Judge scale against
  that, and say which load you assumed.

## 2. Look for

1. **Bug:** wrong result, crash, missed edge case (empty, zero, last item,
   rounding, time zones), a caller broken by the change, a fix applied in one
   caller while the shared function stays broken.
2. **Risk:** security holes (injection, weak randomness, secrets, missing
   checks on input from users), data loss (errors swallowed, writes in the
   wrong order, no transaction).
3. **Scale:** fine for one user, wrong for many: check-then-write races, the
   same work done by every process, memory or lists that only grow, a query
   per item, O(n^2) on big input, per-process state that must be shared.
4. **Missing test:** risky new logic (a branch, a parser, money, security,
   data writes, a bug fix) with no test that fails when it breaks. One good
   test, not coverage.
5. **Speed:** big slowdowns are problems. Small wins (work repeated in a hot
   loop) are suggestions; some software counts every millisecond.
6. **Lean:** code that should not exist or should be smaller.
   - delete: dead code, unused options, speculative features
   - reuse: the repo already has this helper (name the path)
   - stdlib / native: the standard library or platform already does it; a
     new dependency for a few lines
   - yagni: abstraction with one implementation, config nobody sets
   - merge: near-copies that must change together
   - split: one function doing several unrelated jobs, so it is hard to read
     or test. Split by job, never by line count, and never into helpers that
     exist only to make a function shorter.

## 3. Check before you report

- Every finding needs a concrete case: "this input or situation leads to this
  wrong result". No case, no finding.
- Re-read the lines and confirm: the caller ex

_meta.json

{
  "ownerId": "kn75jhs1s4186aj57w94eykzm188rxj8",
  "slug": "ponytail-review",
  "version": "5.1.0",
  "publishedAt": 1791476491860
}

skill-card.md

## Description:

Reviews code changes for bugs, security risks, load issues, missing tests, performance problems, and unnecessary complexity, with actionable findings.

This skill is ready for commercial/non-commercial use.

## Publisher:

[dietrichgebert](https://clawhub.ai/user/dietrichgebert)

### License/Terms of Use:

MIT-0

## Use Case:

Developers and engineers use this skill to review a diff, branch, pull request, or files and receive prioritized, concrete findings without changing code.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Review findings may be incomplete or incorrect.

Mitigation: Check the cited code and proposed fixes before acting on the report.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/dietrichgebert/skills/ponytail-review)
- [Project homepage](https://github.com/DietrichGebert/ponytail)

## Skill Output:

**Output Type(s):** [Markdown]

**Output Format:** [Markdown report with prioritized findings, fixes, and a verdict]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Reports findings only; does not change files.]

## Skill Version(s):

5.1.0 (source: ClawHub release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

Github ReposUpdated 10h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW

Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular