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Thought Leadership

Community
anotb
thought-leadership

Develop evidence-backed points of view, white papers, case studies, industry briefs, and research reports for a consulting audience. Use to turn research or permitted engagement experience into a useful, defensible argument.

Overview

Publisheranotb
Repositorymanagement-consulting-plugin
Skill namethought-leadership
Stars
62
Forks
9
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Thought Leadership 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/anotb/management-consulting-plugin/tree/main/skills/thought-leadership
  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/anotb/management-consulting-plugin.git /tmp/management-consulting-plugin
mkdir -p .claude/skills
cp -r /tmp/management-consulting-plugin/skills/thought-leadership .claude/skills/thought-leadership
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Thought Leadership 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 Thought Leadership 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 Thought Leadership 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.

Thought Leadership

Produce a useful perspective that a practitioner can defend and act on. Match the user's audience, publication format, voice, length, and business purpose. A thesis earns its place through evidence and decision relevance; it does not need to be provocative or contrarian.

Use the research, firm experience, and approved cases provided. Identify missing evidence and draft what is supportable. Ask only when a missing answer determines the piece's meaning or permitted use. Do not invent engagement counts, research findings, quotes, customer results, or claims about what other firms have observed.

Develop the thesis

State the argument and where it applies. Identify the decision it changes, the mechanism, the boundary conditions, and the strongest supported alternative explanation. A broad trend summary may need a sharper question; do not manufacture disagreement to make it distinctive.

For each consequential factual claim, keep the source, date, population, method where relevant, and limitation. Separate empirical findings, a proposed mechanism, forecast, and opinion. “Organizations that do X tend to see Y” and “research suggests” still need evidence. When sources conflict, explain the difference or preserve the uncertainty.

Use current primary sources when the topic requires research and tools are available. Do not imply research has been performed when it has not. A useful evidence-limited draft can identify which claims need support and state a narrower thesis.

Build the asset

Use content formats and evidence for POVs, white papers, case studies, industry briefs, and research reports. Choose the format the user requested and adapt its structure; section lengths and counts are not fixed quotas.

Make a specific managerial argument: what should the reader decide or do differently, and why does this evidence support that advice? Keep the argument central when evidence is limited. State material qualifications concisely beside the relevant claim; put source and approval housekeeping in a reviewer note. Do not fill the piece with repeated warnings or generic advice to collect more data. Connect findings to the implications for the reader. Include the counterargument when it has evidence or a plausible mechanism, and explain the conditions under which it changes the recommendation. Prefer a precise supported observation to a dramatic unsupported statistic.

Use visuals where they clarify a relationship or compress evidence. Trace chart values to sources and distinguish actuals from forecasts. For a requested file, use available creation tools and inspect the result; the skill does not require another plugin.

Use engagement experience accurately

Use only substantiated experience with permitted attribution. A named case can remain named when the user supplies the appropriate approved context. For anonymization, remove or generalize identifying details without changing material industry, scale, timing, or causal facts. If multiple cases are combined or facts materially altered, label the example as composite or hypothetical and do not present its numbers as measured results.

Distinguish drafting from publication. Respect supplied contract, client-consent, quotation, and internal review requirements at the relevant stage; preparing a reviewable draft need not wait for publication approval. Do not publish, contact clients, or claim approval without authorization. Anonymization alone does not establish that publication is permitted.

Review and deliver

Check that the thesis follows from the evidence, examples are truthful and appropriately attributed, limitations are visible, and recommendations fit the audience's ability to act. Remove generic openings, invented opposition, causal overclaims, and repetitive conclusions. Make the piece stand alone without inflating the firm's experience.

State any material evidence or approval gap that affects intended use. For a research report, preserve methodology and uncertainty rather than turning it into promotional copy. For a short POV, retain the argument and practical implication without appending a full research process.

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 Thought Leadership AI skill do?

Develop evidence-backed points of view, white papers, case studies, industry briefs, and research reports for a consulting audience. Use to turn research or permitted engagement experience into a useful, defensible argument.

Why use Thought Leadership on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anotb/management-consulting-plugin/tree/main/skills/thought-leadership. 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 Thought Leadership?

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 Thought Leadership?

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

Is the Thought Leadership AI skill free?

Yes. It is published on GitHub by anotb 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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