Calibrate

Community

sharpdeveye

calibrate

Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.

Overview

Publisher	sharpdeveye
Repository	`maestro`
Skill name	`calibrate`
Stars	591
Forks	73
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/sharpdeveye/maestro/tree/main/source/skills/calibrate
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.

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/calibrate .claude/skills/calibrate

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Calibrate 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 Calibrate 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 Calibrate 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 prompt-engineering reference in the agent-workflow skill for naming and style consistency patterns.

Ensure consistency across all workflow components. Inconsistency creates confusion — for the model, for developers, and for users.

Calibration Dimensions

Naming Conventions

Tool names follow consistent pattern (verb_noun, noun.verb, or camelCase — pick one)
Agent names follow consistent pattern
Configuration keys follow consistent pattern
File names follow consistent pattern

Prompt Style

All prompts use the same structural pattern (4-zone)
Consistent delimiter style (XML tags, markdown headers, triple-dash)
Consistent output schema format (JSON schema, markdown template)
Consistent instruction style (imperative, numbered steps)

Error Handling

All tools return errors in the same format
Error codes follow consistent scheme
Error messages follow consistent tone
Retry logic uses consistent strategy

Logging

All logs use the same format (JSON structured, text, etc.)
Consistent field names across all log entries
Consistent log levels (debug, info, warn, error)
Consistent PII redaction approach

Calibration Process

Identify the standard: What's the most common pattern in the existing codebase? That's the standard.
List deviations: Find all components that deviate from the standard.
Prioritize: Fix the most impactful deviations first (user-facing > internal).
Apply: Make the changes, ensuring tests still pass.
Document: Update .maestro.md with the established conventions.

Consistency Audit Table

Dimension	Standard	Deviations Found	Priority
Tool naming	?	? of ? tools	High/Med/Low
Prompt structure	?	? of ? prompts	High/Med/Low
Error format	?	? of ? tools	High/Med/Low
Log format	?	? of ? entries	High/Med/Low

Calibration Checklist

Convention standard identified for each dimension
All deviations listed with location
Highest impact deviations fixed first
Tests pass after each calibration change
Updated .maestro.md with established conventions

Recommended Next Step

After calibration, run /refine for a final polish pass, or /evaluate to verify consistency improvements.

NEVER:

Invent new conventions when existing ones work
Calibrate in a way that changes behavior (this is standardization, not refactoring)
Skip test verification after calibration
Change naming conventions without updating all references

Frequently asked questions

What does the Calibrate AI skill do?

Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.

Why use Calibrate on TypingMind?

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

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

Which AI models can use Calibrate?

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 Calibrate?

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

Is the Calibrate 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

MANDATORY PREPARATION

Calibration Dimensions

Calibration Process

Consistency Audit Table

Calibration Checklist

Recommended Next Step

Frequently asked questions

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