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Research Brief

Organization
runxhq
research-brief

Produce a decision-ready research-brief brief from bounded governed evidence and preserve every material source binding.

Overview

Publisherrunxhq
Repositoryrunx
Skill nameresearch-brief
Stars
105
Forks
109
Bundled files
6
LicenseApache-2.0
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by runxhq on GitHub. Read the source before you install it.

Installation

Install the Research Brief 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/runxhq/runx/tree/main/skills/research-brief
  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/runxhq/runx.git /tmp/runx
mkdir -p .claude/skills
cp -r /tmp/runx/skills/research-brief .claude/skills/research-brief
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Research Brief 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 Brief 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 Brief 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 Brief

Turn one important question into a durable operator brief: what the answer is, what evidence supports it, what remains uncertain, and what posture the reader should take next. Use this when a quick answer is too shallow but an open-ended report would obscure the decision.

The output should feel like a thoughtful memo, not a narration of the research process. It leads with the decision and operational implication, then exposes the evidence, inference, alternatives, and unresolved questions that justify that posture.

Composes

  • ghostwrite#draft
  • research#local-files
  • research#research

When to use it

Use research-brief for architecture choices, market or ecosystem questions, product bets, trust decisions, or other consequential analysis that needs a reader-ready synthesis. Use plain research when the evidence packet itself is the desired artifact. Use content-package when the primary outcome is public content for a known channel.

Do not use this skill for an unbounded literature review, a daily trend recap, or research whose sources have not been fetched through a governed reader.

How the chain works

  1. The caller supplies the exact question and audience plus either governed source packets or bounded local paths. The local-files runner reads those paths through Runx's native filesystem boundary; it does not tunnel local evidence through HTTP.
  2. The canonical research skill admits and indexes those sources, separates evidence from inference, and verifies every citation and recommendation.
  3. Only a ready research packet proceeds to ghostwrite. The writing stage turns decision support into a clear brief without introducing unsupported facts.
  4. The final artifact preserves the research and content packet bindings. It remains local and is not a publication claim.

Local research and drafting need no approval because they do not cross an external boundary. If the brief is later sent, posted, or published, the provider delivery skill owns approval, idempotency, acknowledgement, and readback.

Inputs and result

  • objective is the exact decision question.
  • source_packets are bounded governed evidence. The local-files runner accepts bounded paths below a selected local root instead. Operator context, URLs, bare paths, and model memory do not substitute for admitted evidence.
  • audience and channel shape the memo's presentation.
  • domain, operator_context, and target_entities keep the analysis scoped but do not count as evidence.

The result contains the citation-validated research_packet and, when evidence is ready, the evidence-bound content_draft_packet. It may finish at needs_more_evidence or not_worth_publishing rather than manufacture a memo.

Stop conditions

  • Stop before drafting when no valid source survives research admission.
  • Preserve uncertainty that could change the recommendation.
  • Do not turn operator preference into a verified market or product fact.
  • Do not add a publish or delivery state to a local brief.
  • Route any outward action to its owning provider skill with the exact artifact digest and evidence packet intact.

Example

For “Should this provider become a native Runx tool?”, the source set might include its official API contract, two existing consumer implementations, and runtime measurements. The brief should recommend native ownership, package ownership, or no change; show which evidence supports that boundary; and name the remaining operational risk. It should not become a generic provider profile or imply adoption merely because the API exists.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Research Brief AI skill do?

Produce a decision-ready research-brief brief from bounded governed evidence and preserve every material source binding.

Why use Research Brief on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/runxhq/runx/tree/main/skills/research-brief. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Research Brief?

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 Brief?

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

Is the Research Brief AI skill free?

Yes. It is published on GitHub by runxhq under the Apache-2.0 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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