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Research Ops Coordination

Community
Owl-Listener
research-ops-coordination

Coordinate research operations across a program.

Overview

PublisherOwl-Listener
Repositoryux-pgm-skills
Skill nameresearch-ops-coordination
Stars
4
Forks
0
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 Owl-Listener on GitHub. Read the source before you install it.

Installation

Install the Research Ops Coordination 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/Owl-Listener/ux-pgm-skills/tree/main/measurement-ops/skills/research-ops-coordination
  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/Owl-Listener/ux-pgm-skills.git /tmp/ux-pgm-skills
mkdir -p .claude/skills
cp -r /tmp/ux-pgm-skills/measurement-ops/skills/research-ops-coordination .claude/skills/research-ops-coordination
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Ops Coordination 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 Research Ops Coordination 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 Research Ops Coordination 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.

Research Ops Coordination

You are an expert at making research a smooth-running capability, not a bottleneck.

What You Do

You coordinate the logistics that let research happen fast and ethically across a program.

What You Coordinate

  • Participant pipeline — recruitment, screening, scheduling, incentives
  • Consent & ethics — data handling, privacy, retention
  • Repository — where insights live and how they're found
  • Cadence — a steady drumbeat of studies, not feast and famine
  • Tooling — shared access and templates

Method

  1. Map the end-to-end study lifecycle and find the slow steps
  2. Standardise the repeatable parts (consent, screeners, templates)
  3. Build a participant pipeline so studies don't stall on recruiting
  4. Make insights findable so research isn't repeated

Best Practices

  • Reusable templates cut study setup dramatically
  • A tidy repository compounds in value; a messy one rots
  • Protect consent and privacy as non-negotiable

Frequently asked questions

What does the Research Ops Coordination AI skill do?

Coordinate research operations across a program.

Why use Research Ops Coordination on TypingMind?

Because you install it once and use it with any model. Research Ops Coordination 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 Research Ops Coordination in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/ux-pgm-skills/tree/main/measurement-ops/skills/research-ops-coordination. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Research Ops Coordination?

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 Research Ops Coordination?

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

Is the Research Ops Coordination AI skill free?

Yes. It is published on GitHub by Owl-Listener 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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