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S4h Historical Precedent Analysis

Organization
human-avatar
s4h-historical-precedent-analysis

Finds and applies genuinely similar historical situations to inform a current decision — distinguishing true precedents from superficial analogies. TRIGGERS: 'historical precedent', 'has this happened before', 'what does history say', 'find a precedent', 'what did others do in this situation'.

Overview

Publisherhuman-avatar
Repositoryskills-for-humanity
Skill names4h-historical-precedent-analysis
Stars
234
Forks
24
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 human-avatar on GitHub. Read the source before you install it.

Installation

Install the S4h Historical Precedent Analysis 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/human-avatar/skills-for-humanity/tree/main/skills/s4h-historical-precedent-analysis
  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/human-avatar/skills-for-humanity.git /tmp/skills-for-humanity
mkdir -p .claude/skills
cp -r /tmp/skills-for-humanity/skills/s4h-historical-precedent-analysis .claude/skills/s4h-historical-precedent-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable S4h Historical Precedent 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 S4h Historical Precedent 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 S4h Historical Precedent 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.

Historical Precedent Analysis

History doesn't repeat — but structures do. The error is searching for surface similarity (same industry, same technology, same geography) and missing structural similarity (same underlying dynamics, same constraint set, same incentive conflicts). Superficial precedents produce false confidence. Structural precedents produce genuine insight. This skill finds the real ones.


Your Process

Step 1: Abstract the Situation Strip away domain-specific language and surface details. What is the underlying structural pattern? Describe it in terms that could apply across industries and eras: a new entrant facing incumbents with switching-cost moats; a coalition with aligned goals but divergent interests trying to coordinate; a technology displacing a profession whose members control the adoption decision. State the situation in these structural terms — this is what you'll search for in history.

Framing check: Confirm the specific situation before continuing. State what you've identified — the actual situation being analyzed and its core structural pattern — in one sentence, then use AskUserQuestion:

  • Question: "I'm reading this as: [your one-sentence structural framing of the situation]. Is that right?"
  • Header: "Framing"
  • Options:
    • Yes — proceed — framing is correct
    • Adjust — one element is off; user will correct it before you continue
    • Reframe — different situation than read; incorporate the correction before proceeding

Step 2: Search for Structural Precedents Deliberately look outside the obvious domain. The most obvious precedent (same industry, earlier decade) usually has the most surface similarity and the least structural insight — the surface differences are visible but the structural similarities are already assumed. Search across industries, eras, and scales for situations with the same underlying dynamics.

Before narrowing: Show the complete generated set to the user first. Use AskUserQuestion:

  • Question: "I've identified [N] candidate precedents. Before I select the most structurally similar, are there any you'd flag as especially important, or any I've missed?"
  • Header: "Prioritise"
  • Options:
    • Proceed with your selection — the set looks right
    • Flag one — user will name a specific precedent to include
    • Add a missing one — user will describe it

Then find 2-3 with the strongest structural match.

Step 3: Describe Each Precedent For each: what was the specific situation, what approaches were tried, what was the outcome? Be concrete — vague historical reference ("like the industrial revolution") is not a precedent. A precedent is a specific case with specific decisions and specific results.

Step 4: Structural Mapping For each precedent: where does the structural similarity hold most clearly? Where does it break down? What are the key variables that differ between the historical case and the current situation — and how might those differences change what the precedent implies?

Step 5: Extract the Lesson Not "do what they did" — that's surface imitation that ignores structural differences. The lesson is: what does their experience suggest matters most in this type of situation? What was the decisive variable? What would have changed the outcome if it had been different?


Human Check-in

Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:

  • Question: "My read: [your 1–2 sentence interpretation]. How do you want to proceed?"
  • Header: "Scope"
  • Options:
    • Full analysis — Complete all steps, reasoning shown throughout
    • Key findings only — Bottom-line output, skip step-by-step detail
    • Closest precedent only — The single most structurally similar historical case, fully developed
    • Reframe — The read is off; correct it and the analysis will follow the corrected framing

Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.

Output Format

Situation (Abstracted): [structural description in domain-neutral terms]

Precedents

PrecedentWhat/WhenWhat Was TriedOutcome
[descriptive name][specific context][approach taken][what happened]

Structural Mapping

PrecedentWhere It MapsWhere It DivergesKey Differing Variables
[name][structural overlap][structural gap][variables that differ]

Lesson: [the transferable principle — the underlying rule, stated without domain-specific language]

Caveats: [where the precedent fails to apply and what would need to be different for it to hold]


Notes

The strongest precedent is often the most surprising one — from a completely different domain that shares the underlying dynamics. Don't default to the obvious comparison within the same industry. The abstractions done in Step 1 determine the quality of everything that follows — spend time there.


What's Next

After delivering this output, use AskUserQuestion to offer the next move:

  • Question: "Precedents analysed. What's next?"
  • Header: "Next"
  • Options:
    • /s4h-historical-lesson-extraction — Extract lessons from the precedents found
    • /s4h-decision-criteria-weighting — Weight criteria against precedent outcomes
    • /s4h-strategy-positioning — Position relative to what happened in comparable cases
    • Done — Wrap up and synthesise what we have so far

Frequently asked questions

What does the S4h Historical Precedent Analysis AI skill do?

Finds and applies genuinely similar historical situations to inform a current decision — distinguishing true precedents from superficial analogies. TRIGGERS: 'historical precedent', 'has this happened before', 'what does history say', 'find a precedent', 'what did others do in this situation'.

Why use S4h Historical Precedent Analysis on TypingMind?

Because you install it once and use it with any model. S4h Historical Precedent 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 S4h Historical Precedent Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/human-avatar/skills-for-humanity/tree/main/skills/s4h-historical-precedent-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use S4h Historical Precedent 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 S4h Historical Precedent Analysis?

As many as you like. As long as a model supports skills, you can use S4h Historical Precedent Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the S4h Historical Precedent Analysis AI skill free?

Yes. It is published on GitHub by human-avatar 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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