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Egret

Organization
Power-Agent
egret

Progressive-disclosure workflow for Egret market and operations optimization. Use whenever the user wants to run DC-OPF, AC-OPF, or unit commitment through PowerMCP — even when they just say "what's the cheapest dispatch", "commit the units", "check for congestion", or "is this schedule feasible". Exposes the simplest credible optimization (DC-OPF) before escalating to AC-OPF or full unit commitment. Reach for this instead of answering Egret optimization questions unaided.

Overview

PublisherPower-Agent
RepositoryPowerSkills
Skill nameegret
Stars
77
Forks
23
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepository
  • 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 Power-Agent on GitHub. Read the source before you install it.

Installation

Install the Egret 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/Power-Agent/PowerSkills/tree/main/powerskills-tool/skills/egret
  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/Power-Agent/PowerSkills.git /tmp/PowerSkills
mkdir -p .claude/skills
cp -r /tmp/PowerSkills/powerskills-tool/skills/egret .claude/skills/egret
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Egret 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 Egret 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 Egret 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.

Egret workflow

Start with the cheapest model that can answer the question. Do not jump into unit commitment when a single-snapshot OPF will do.

Default tool ladder

  1. solve_dc_opf(case_file, solver, return_results) for fast feasibility and congestion screening.
  2. solve_ac_opf(case_file, solver, return_results) when voltage or reactive realism matters.
  3. solve_unit_commitment_problem(case_file, solver, mipgap, timelimit) only after the horizon, reserve logic, and commitment assumptions are clear.

Working rules

  • Confirm the case file format, solver, and time horizon before solving.
  • Use DC OPF first unless the question explicitly depends on AC feasibility.
  • Treat UC as a higher-cost study that needs a clear operational objective.
  • Validate promising dispatch fixes in an AC tool when voltage limits matter.

Escalation triggers

Quote the binding constraint or infeasibility cause rather than saying "it failed".

ObservationEscalate to
OPF or UC infeasible, reserve-short, or implausibly expensiveoperations-planning-mitigation
AC-OPF bus voltage outside [0.95, 1.05] puvoltage-violation-mitigation
A branch limit binds persistently across the horizonthermal-overload-mitigation

Deliver

  • The case, solver, and study type.
  • The limiting constraints or binding tradeoffs.
  • Whether the next step is AC validation, UC escalation, or mitigation.

Frequently asked questions

What does the Egret AI skill do?

Progressive-disclosure workflow for Egret market and operations optimization. Use whenever the user wants to run DC-OPF, AC-OPF, or unit commitment through PowerMCP — even when they just say "what's the cheapest dispatch", "commit the units", "check for congestion", or "is this schedule feasible". Exposes the simplest credible optimization (DC-OPF) before escalating to AC-OPF or full unit commitment. Reach for this instead of answering Egret optimization questions unaided.

Why use Egret on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Power-Agent/PowerSkills/tree/main/powerskills-tool/skills/egret. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Egret?

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 Egret?

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

Is the Egret AI skill free?

Yes. It is published on GitHub by Power-Agent 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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