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Streamline

Community
sharpdeveye
streamline

Use when the workflow feels too complex, has accumulated cruft, or has redundant steps and overlapping tools that need consolidation.

Overview

Publishersharpdeveye
Repositorymaestro
Skill namestreamline
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 Streamline 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/streamline
  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/streamline .claude/skills/streamline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Streamline 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 Streamline 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 Streamline 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 agent-architecture reference in the agent-workflow skill for complexity assessment and topology simplification.


Reduce complexity without reducing capability. Every component should earn its place.

Streamlining Analysis

For each component, ask:

  1. Does this add measurable value? If you can't name the specific value, remove it.
  2. Can this be combined with another component? Merge overlapping responsibilities.
  3. Is this solving a real problem or an imagined one? Remove speculative complexity.
  4. Would a simpler alternative work? Prefer simplicity over elegance.

Common Streamlining Targets

Pipeline Steps

  • Remove steps that transform data without changing it meaningfully
  • Combine sequential steps that could be one prompt
  • Eliminate validation steps that duplicate downstream validation

Tool Consolidation

  • Merge tools that operate on the same data with different filters
  • Remove tools the model never selects (check usage logs)
  • Combine read tools with similar signatures

Prompt Simplification

  • Remove instructions the model follows by default
  • Consolidate redundant constraints
  • Shorten few-shot examples to minimum viable length

Configuration Reduction

  • Remove config parameters that always use the default
  • Hardcode values that never change between environments
  • Merge related config into logical groups

Streamlining Report

For each recommendation:

  1. What to remove/simplify — specific component or code
  2. Why it's safe — what ensures functionality is preserved
  3. Expected impact — latency reduction, cost reduction, or maintainability improvement

Complexity Score

ComponentCurrentMinimal ViableAction
Pipeline steps??Remove/merge ?
Tools??Consolidate ?
Config params??Remove ?
Agent count??Collapse ?

Streamlining Checklist

  • Each component justified with concrete value
  • Redundant steps identified and marked for removal
  • Tool usage logs checked for never-used tools
  • Golden test set passes after each simplification
  • No safety guardrails, logging, or error handling removed

Recommended Next Step

After streamlining, run /evaluate to verify functionality is preserved, then /refine for final polish.

NEVER:

  • Remove error handling in the name of simplicity
  • Streamline without verifying the golden test set still passes
  • Remove logging or observability
  • Simplify below the level of correctness
  • Remove safety guardrails

Frequently asked questions

What does the Streamline AI skill do?

Use when the workflow feels too complex, has accumulated cruft, or has redundant steps and overlapping tools that need consolidation.

Why use Streamline on TypingMind?

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

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

Which AI models can use Streamline?

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 Streamline?

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

Is the Streamline 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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