Insight Synthesis

Community

nimrodfisher

insight-synthesis

Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.

Overview

Publisher	nimrodfisher
Repository	`data-analytics-skills`
Skill name	`insight-synthesis`
Stars	493
Forks	87
Bundled files	3
License	MIT
Links	Skill source Repository

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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by nimrodfisher on GitHub. Read the source before you install it.

Installation

Install the Insight Synthesis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/nimrodfisher/data-analytics-skills/tree/main/04-data-storytelling-visualization/insight-synthesis
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/nimrodfisher/data-analytics-skills/tree/main/04-data-storytelling-visualization/insight-synthesis

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/nimrodfisher/data-analytics-skills.git /tmp/data-analytics-skills
mkdir -p .claude/skills
cp -r /tmp/data-analytics-skills/04-data-storytelling-visualization/insight-synthesis .claude/skills/insight-synthesis

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Insight Synthesis 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 Insight Synthesis 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 Insight Synthesis 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.

Insight Synthesis

When to use

An analysis has produced many statistics but no clear "so what"
The team has findings but is struggling to prioritise which ones to act on
Stakeholders are asking "what does this mean for us?" rather than "what did you find?"
Multiple analyses need to be synthesised into a unified set of recommendations
Preparing an insight briefing for a team that doesn't have time to review the full analysis

Process

List all findings — enumerate every statistically meaningful finding: trends, comparisons, correlations, anomalies, surprises. Write each as a factual statement. Don't interpret yet.
Apply So What → Why → Now What to each finding — convert each fact into an insight by answering: So what (why does this matter to the business?), Why (what is the most likely explanation?), Now what (what specific action should follow?). See references/insight_framework.md.
Quantify business impact — for each insight, estimate the financial, customer, or operational magnitude. An insight without a number is an observation. Use order-of-magnitude estimates if precise data is not available.
Prioritise by impact × confidence × actionability — score each insight on these three dimensions (1–3 scale). Insights that score high on all three are the ones to lead with. Deprioritise insights that are high-impact but low-confidence until validated.
Group and resolve conflicts — cluster related insights and check for contradictions. If two findings point in opposite directions, document the tension and state what additional data would resolve it.
Produce the insight brief — present the top 3–5 insights in priority order, each with the finding, So What / Why / Now What, business impact, and confidence level. Use assets/insight_brief_template.md.

Inputs the skill needs

All analysis findings (statistics, charts, model outputs, anomalies)
Business context: current goals, OKRs, strategic priorities
Audience who will act on the insights (role and decision authority)
Confidence levels for the findings (based on sample size, method, data quality)
Known constraints on action (budget, timeline, team capacity)

Output

references/insight_framework.md — So What / Why / Now What pattern, insight quality rubric, prioritisation matrix
references/prioritization_guide.md — scoring insights by impact, confidence, and actionability; how to present trade-offs
assets/insight_brief_template.md — structured brief: top insights in priority order, each with impact, explanation, recommendation, and confidence level

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 Insight Synthesis AI skill do?

Why use Insight Synthesis on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nimrodfisher/data-analytics-skills/tree/main/04-data-storytelling-visualization/insight-synthesis. 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 Insight Synthesis?

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 Insight Synthesis?

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

Is the Insight Synthesis AI skill free?

Yes. It is published on GitHub by nimrodfisher 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.

View all

Ui Styling

nextlevelbuilder

OrganizationPopular

Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user…

Landing Report

Read-only queue dashboard for workspace-aware ship. (gstack)

Gstack Openclaw Ceo Review

garrytan

CommunityPopular

Use when asked to review a plan, challenge a proposal, run a CEO review, poke holes in an approach, think bigger about scope, or decide whether to expand or reduce the plan.

Caveman Stats

Show recorded output and cache-read token usage and mode attribution for the current Claude Code session, or locate the host's native usage report. Trigger: /caveman-stats.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Insight Synthesis

When to use

Process

Inputs the skill needs

Output

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now