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Fortify

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sharpdeveye
fortify

Use when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.

Overview

Publishersharpdeveye
Repositorymaestro
Skill namefortify
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 Fortify 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/fortify
  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/fortify .claude/skills/fortify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fortify 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 Fortify 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 Fortify 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 defense-in-depth patterns and error boundary design.


Make the workflow resilient. Every external call will fail eventually — model APIs, tools, databases, third-party services. Fortify ensures the workflow handles failure gracefully.

Fortification Layers

Layer 1: Input Validation

  • Validate all inputs before processing
  • Return clear error messages for invalid input
  • Set size limits on all input fields

Layer 2: Retry with Backoff For transient failures (network errors, rate limits, timeouts):

yaml
Retry strategy:
  max_retries: 3
  initial_delay: 1s
  backoff_multiplier: 2
  max_delay: 30s
  retryable_errors: [429, 500, 502, 503, 504, TIMEOUT, CONNECTION_ERROR]
  non_retryable_errors: [400, 401, 403, 404]

Layer 3: Fallback Responses When retries are exhausted:

  • Use a cached previous response (if applicable)
  • Use a simpler/cheaper model as fallback
  • Return a graceful degradation response
  • Escalate to human review

Layer 4: Circuit Breakers When a service is consistently failing:

yaml
Circuit breaker:
  failure_threshold: 5 consecutive failures
  state: CLOSED → OPEN (after threshold) → HALF_OPEN (after cooldown)
  cooldown: 60 seconds
  half_open_max_requests: 1

Layer 5: Timeout Controls Every external call needs a timeout:

  • Model API calls: 30-120s depending on task
  • Tool executions: 10-60s depending on tool
  • Database queries: 5-15s
  • Third-party APIs: 10-30s

Fortification Audit

For each component, verify:

  • Input validation present
  • Retry logic for transient failures
  • Fallback for when retries fail
  • Timeout set
  • Error logged with context
  • User gets a meaningful error (not a stack trace)

Recommended Next Step

After fortification, run /evaluate to verify error handling works under realistic failure scenarios.

NEVER:

  • Retry non-retryable errors (authentication failures, validation errors)
  • Retry without backoff (you'll make the problem worse)
  • Swallow errors silently (log and handle, don't ignore)
  • Set infinite timeouts (they'll hang forever)
  • Skip the fallback (retries exhausted with no fallback = user sees an error)

Frequently asked questions

What does the Fortify AI skill do?

Use when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.

Why use Fortify on TypingMind?

Because you install it once and use it with any model. Fortify 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 Fortify in TypingMind?

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

Which AI models can use Fortify?

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 Fortify?

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

Is the Fortify 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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