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mustang

OpenHoof is a personal AI agent you run on your own devices. No guardrails. No filters. No corporate safety theater. Just a raw, unbroken stallion of an AI. Lives on WhatsApp, Telegram, Slack, Discord, Signal & 20+ more channels. Local, fast, always-on, stubbornly uncensored.

Install / Use

npx skills add OpenHoof-AI/OpenHoof --skill mustang

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

71/100

Category

Automation

Supported Platforms

Universal

Our assessment of mustang

mustang scores 71/100 on our quality scale, 2493rd of 2,864 Automation skills we index.

Its SKILL.md is 2.6 KB long, well organised into 10 sections with 6 code examples: a solid amount of guidance for an agent.

It has no GitHub stars yet, so there is no community track record; judge it on its content.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
0/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 74/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-01. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

mustang compared with similar skills

All 4 of these similar skills score higher than mustang; compare them before choosing.

SkillScoreStarsUpdatedFormat
mustang (this skill)by OpenHoof-AI7107mo agoSKILL.md
Agent-Reachby Panniantong10087.2k16d agoCLAUDE.md
rufloby ruvnet10073.6ktodayCLAUDE.md
Scraplingby D4Vinci10085.0k1d agoMCP Server
algorithmic-artby anthropics100177.9k9d agoSKILL.md

Frequently asked questions

How do I install mustang?
Run npx skills add OpenHoof-AI/OpenHoof --skill mustang. The install tabs above show the steps for each supported agent.
Which AI agents does mustang work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is mustang safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It declares no license and scores 74/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is mustang still maintained?
The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

Mustang

Mustang executes multi-step workflows with approval checkpoints. Use it when:

  • User wants a repeatable automation (triage, monitor, sync)
  • Actions need human approval before executing (send, post, delete)
  • Multiple tool calls should run as one deterministic operation

When to use Mustang

| User intent | Use Mustang? | | ------------------------------------------------------ | --------------------------------------------- | | "Triage my email" | Yes — multi-step, may send replies | | "Send a message" | No — single action, use message tool directly | | "Check my email every morning and ask before replying" | Yes — scheduled workflow with approval | | "What's the weather?" | No — simple query | | "Monitor this PR and notify me of changes" | Yes — stateful, recurring |

Basic usage

Run a pipeline

{
  "action": "run",
  "pipeline": "gog.gmail.search --query 'newer_than:1d' --max 20 | email.triage"
}

Returns structured result:

{
  "protocolVersion": 1,
  "ok": true,
  "status": "ok",
  "output": [{ "summary": {...}, "items": [...] }],
  "requiresApproval": null
}

Handle approval

If the workflow needs approval:

{
  "status": "needs_approval",
  "output": [],
  "requiresApproval": {
    "prompt": "Send 3 draft replies?",
    "items": [...],
    "resumeToken": "..."
  }
}

Present the prompt to the user. If they approve:

{
  "action": "resume",
  "token": "<resumeToken>",
  "approve": true
}

Example workflows

Email triage

gog.gmail.search --query 'newer_than:1d' --max 20 | email.triage

Fetches recent emails, classifies into buckets (needs_reply, needs_action, fyi).

Email triage with approval gate

gog.gmail.search --query 'newer_than:1d' | email.triage | approve --prompt 'Process these?'

Same as above, but halts for approval before returning.

Key behaviors

  • Deterministic: Same input → same output (no LLM variance in pipeline execution)
  • Approval gates: approve command halts execution, returns token
  • Resumable: Use resume action with token to continue
  • Structured output: Always returns JSON envelope with protocolVersion

Don't use Mustang for

  • Simple single-action requests (just use the tool directly)
  • Queries that need LLM interpretation mid-flow
  • One-off tasks that won't be repeated

Related Skills

View on GitHub
GitHub Stars0
CategoryAutomation
Updated6mo ago
Forks0

Trust signals

74/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium2 low