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Guard

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sharpdeveye
guard

Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.

Overview

Publishersharpdeveye
Repositorymaestro
Skill nameguard
Stars
591
Forks
73
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by sharpdeveye on GitHub. Read the source before you install it.

Installation

Install the Guard AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sharpdeveye/maestro/tree/main/source/skills/guard
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sharpdeveye/maestro.git /tmp/maestro
mkdir -p .claude/skills
cp -r /tmp/maestro/source/skills/guard .claude/skills/guard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Guard in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Guard on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Guard is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MANDATORY PREPARATION

Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first.

Consult the guardrails-safety reference in the agent-workflow skill for the full defense-in-depth framework.


Add safety boundaries to a workflow. Guards protect against malicious inputs, unintended outputs, data leakage, cost explosion, and all the ways an autonomous system can go wrong in the real world.

Threat Assessment

Before adding guards, understand what you're protecting against:

ThreatRisk LevelGuard Type
Prompt injectionHighInput sanitization, instruction hierarchy
PII leakageHighOutput filtering, data masking
Cost explosionHighToken budgets, rate limits
Unauthorized actionsMediumPermission scoping, confirmation gates
HallucinationMediumSource attribution, fact checking
Service abuseMediumRate limiting, authentication

Guard Implementation

Input Guards

text
Before processing any input:
1. Validate against schema (reject malformed)
2. Check size limits (reject oversized)
3. Sanitize for injection patterns
4. Rate limit check (reject if exceeded)
5. Authentication/authorization check

Output Guards

text
Before returning any output:
1. Schema validation (format correct?)
2. PII scan (names, emails, SSNs, etc.)
3. Content policy check
4. Confidence threshold check
5. Source attribution present?

Cost Guards

text
Before every model/API call:
1. Check remaining budget
2. Estimate request cost
3. If estimate > remaining budget → reject or use cheaper alternative
4. After call → update spent amount
5. Circuit breaker check (too many failures?)

Permission Guards

text
For every tool call:
1. Is this tool allowed for this user/context?
2. Is this a destructive operation? → require confirmation
3. Is this accessing data the user is authorized for?
4. Log the access for audit trail

Guard Checklist

  • All inputs validated before processing
  • PII detection on all outputs
  • Cost ceiling set with enforcement
  • Prompt injection defenses active
  • Destructive operations require confirmation
  • All access logged for audit
  • Circuit breakers on external services
  • Rate limits on all endpoints

Recommended Next Step

After adding guards, run /evaluate with adversarial test scenarios to verify guards hold under attack.

NEVER:

  • Deploy without input validation
  • Trust model output for high-stakes decisions without verification
  • Run without cost controls
  • Skip logging (you need the audit trail)
  • Assume the model will follow safety instructions 100% of the time

Frequently asked questions

What does the Guard AI skill do?

Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.

Why use Guard on TypingMind?

Because you install it once and use it with any model. Guard is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Guard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sharpdeveye/maestro/tree/main/source/skills/guard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Guard?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Guard?

As many as you like. As long as a model supports skills, you can use Guard with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Guard AI skill free?

Yes. It is published on GitHub by sharpdeveye under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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