023 Assumption Analysis

Community

jabrena

023-assumption-analysis

Use when a framed and root-caused problem needs its assumptions made explicit before design or planning begins — explicit Assumptions, Unknowns, and a Validation plan. This should trigger when an issue's Assumption Analysis point of view needs evaluation, or when a maintainer directly asks to surface hidden assumptions and unknowns before committing to an approach. Part of Plinth Toolkit

Overview

Publisher	jabrena
Repository	`plinth`
Skill name	`023-assumption-analysis`
Stars	455
Forks	95
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

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 jabrena on GitHub. Read the source before you install it.

Installation

Install the 023 Assumption Analysis 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/jabrena/plinth/tree/main/skills/023-assumption-analysis
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.

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/jabrena/plinth.git /tmp/plinth
mkdir -p .claude/skills
cp -r /tmp/plinth/skills/023-assumption-analysis .claude/skills/023-assumption-analysis

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

Use it in TypingMind

Enable 023 Assumption Analysis 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 023 Assumption Analysis 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 023 Assumption Analysis 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.

Assumption Analysis

Guide production of explicit Assumptions, a list of Unknowns, and a Validation plan for a problem under exploration. This is an interactive SKILL.

What is covered in this Skill?

Surfacing assumptions implicit in the problem frame and root-cause findings
Distinguishing an assumption (believed true, not yet verified) from an unknown (not yet known either way)
Ranking assumptions and unknowns by impact and confidence
Defining a validation plan that names how and when each risky assumption or unknown will be checked
Feeding assumption and unknown findings into 024-context-mapping and the remaining Functional Specification lenses

Constraints

Make assumptions and unknowns explicit before they become undiscussed risk. When this technique is orchestrated by another workflow, the orchestrator owns clarifying-question sequencing; when applied standalone, ask directly.

MUST read references/023-assumption-analysis.md before applying Assumption Analysis guidance
MUST state each assumption as a falsifiable claim believed true but not yet verified
MUST distinguish assumptions (believed true) from unknowns (not yet known either way)
MUST rank assumptions and unknowns by impact if wrong and by current confidence
MUST define a validation plan naming how and when each high-impact, low-confidence assumption or unknown will be checked
MUST NOT invent an assumption, unknown, or validation step when the available content is vague or ambiguous; flag the gap for a clarifying question instead

When to use this skill

Surface the assumptions behind this problem
List the unknowns for this issue
Build a validation plan for these assumptions
Apply assumption analysis before design begins
Draft the Assumption Analysis section of a Functional Specification

Workflow

Read the Reference

Read references/023-assumption-analysis.md, then review the problem frame and root-cause findings for implicit beliefs.

Surface Explicit Assumptions

State each assumption as a falsifiable claim believed true but not yet verified.

List Unknowns

List facts that are not yet known either way, distinct from assumptions.

Rank by Impact and Confidence

Rank assumptions and unknowns by impact if wrong and by current confidence, prioritizing high-impact, low-confidence items.

Define the Validation Plan

Name how and when each high-priority assumption or unknown will be validated.

Report the Assumption Analysis

Report the Assumptions, Unknowns, and Validation plan, and flag any item left open pending a clarifying answer.

Reference

For detailed guidance, examples, and constraints, see references/023-assumption-analysis.md.

Bundled files

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

references/023-assumption-analysis.md6 KB

Frequently asked questions

What does the 023 Assumption Analysis AI skill do?

Why use 023 Assumption Analysis on TypingMind?

Because you install it once and use it with any model. 023 Assumption Analysis 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 023 Assumption Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jabrena/plinth/tree/main/skills/023-assumption-analysis. 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 023 Assumption Analysis?

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 023 Assumption Analysis?

As many as you like. As long as a model supports skills, you can use 023 Assumption Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 023 Assumption Analysis AI skill free?

Yes. It is published on GitHub by jabrena 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Assumption Analysis

Constraints

When to use this skill

Workflow

Reference

Bundled files

Frequently asked questions

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