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Focal Point Finder

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gnurio
focal-point-finder

This skill should be used when someone needs to find, propose, or evaluate a focal point in a coordination, negotiation, or alignment problem. A focal point is a solution that people converge on without explicit agreement — because it is uniquely prominent, simple, or recognizable. Based on Thomas Schelling's "The Strategy of Conflict." Triggers on "where should we align?", "how do we get everyone on the same page?", "what's the obvious choice?", "find a focal point", "Schelling point", "coordination problem", "how do we agree without talking?", "what would everyone pick?", "propose a standard", "set a default", or any situation where multiple parties need to converge on a single choice without full communication.

Overview

Publishergnurio
Repositorynurijanian-skills
Skill namefocal-point-finder
Stars
127
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 gnurio on GitHub. Read the source before you install it.

Installation

Install the Focal Point Finder 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/gnurio/nurijanian-skills/tree/main/skills/focal-point-finder
  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/gnurio/nurijanian-skills.git /tmp/nurijanian-skills
mkdir -p .claude/skills
cp -r /tmp/nurijanian-skills/skills/focal-point-finder .claude/skills/focal-point-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Focal Point Finder 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 Focal Point Finder 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 Focal Point Finder 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.

Focal Point Finder

Identify, evaluate, or create focal points in coordination and negotiation problems using Thomas Schelling's framework from The Strategy of Conflict.

A focal point is not the objectively best outcome. It is the outcome that everyone expects everyone else to expect — the one choice that stands out enough for mutual recognition. The authority is in the expectations themselves, not in the thing expectations attach to.

When to Use

  • Multiple parties need to converge on a single choice (standard, deadline, meeting point, price, boundary, process)
  • Communication is limited, ambiguous, or costly
  • No formal authority can dictate the answer
  • A proposal needs to "stick" without enforcement
  • An existing default needs to be defended or displaced

Step 1: Map the Coordination Problem

Extract the structure of the situation by answering:

  1. Who are the parties? (List every actor who must align)
  2. What is being coordinated? (A location, a number, a standard, a boundary, a process, a date, a format)
  3. What are the communication constraints? (Full communication? Partial? Tacit? Asynchronous? Cross-cultural?)
  4. What happens if they fail to converge? (Cost of miscoordination — this determines urgency)
  5. Are interests aligned, divergent, or mixed? (Pure coordination, bargaining, or mixed-motive)

Present the map to the user for validation before proceeding.

Step 2: Scan for Existing Focal Points

Before proposing anything new, identify what focal points already exist. Check each source:

The Five Magnets

Uniqueness — Is there one option that stands alone, qualitatively different from all others? Test: "If not this, what?" — if there is no clear alternative, it is focal.

Example: On a map with many crossroads but one house, all 11 people who picked the house met. The 4 who picked crossroads each chose a different one and none met. Three houses would have destroyed the focal point — uniqueness avoids ambiguity.

Simplicity — Is there a clean, discrete option vs. many that differ only by degree? Test: "Can this be stated in one sentence without qualifiers?"

Example: Poison gas was not used in WWII despite no formal treaty. "No gas" is binary and unambiguous. "Some gas" (how much? where? against whom?) creates impossible coordination. The simplicity of total abstention made it the only tacitly achievable limit.

Precedent — Has this been done before in a similar situation? Is there a pattern everyone knows? Test: "What happened last time?"

Example: Middle Eastern oil royalties converged on the 50-50 formula within years of the first deal setting that pattern. Subsequent negotiations had "no heart left in the bargaining" under the shadow of that precedent.

Symmetry — Is there a mathematically or aesthetically balanced option (50-50, equal, round numbers)? Test: "Does this feel 'fair' by default?"

Example: Two strangers secretly divide $100 into piles A and B. If splits match, both keep $100. 36 out of 40 chose $50/$50 — not because it is fair, but because it is the only split both can be certain the other will also pick.

Cultural Salience — Is there something that this specific group of people would all recognize as obvious? Test: "Would a newcomer to this group guess the same answer?"

Example: "Meet somewhere in NYC, no instructions." Most chose Grand Central Station, information booth, 12 noon. The answer depends entirely on the people — a sample from Tokyo would converge elsewhere.

For each candidate focal point found, rate its strength:

  • Strong: passes 3+ magnet tests, no competing focal points
  • Moderate: passes 1-2 magnet tests, one or two competitors
  • Weak: arguable, multiple equally valid alternatives exist

If a strong focal point already exists, present it and stop. The user's job is to recognize it, not to invent a new one.

Step 3: Diagnose Why Convergence Is Failing (If It Is)

If there is no existing focal point or the obvious one is being ignored, diagnose why:

SymptomLikely CauseSchelling Remedy
Too many options, no one commitsNo option has qualitative uniquenessStrip away options until one stands alone
Everyone has a different "obvious" answerCultural salience differs across partiesFind common ground — shared precedent, shared reference points
The obvious answer is unfair to one partyThe focal point discriminatesAccept it if miscoordination is worse, or find an equally prominent alternative
Someone introduced conflicting dataNoise is drowning the signalSimplify: remove extraneous variables
The old default was breachedPrecedent was broken without a replacementEstablish a new bright line quickly, before the vacuum fills with chaos
Agreement in principle, but endless debate on degreeTrying to compromise on a continuumFind a qualitative boundary (river, not "some miles")

Step 4: Create or Propose a Focal Point

When no natural focal point exists, create one using these techniques (ordered by reliability).

Key principle: finding a focal point requires imagination, not just logic. Schelling notes that "poets may do better than logicians at this game, which is perhaps more like 'puns and anagrams' than like chess." Accidental arrangements, humor, and even whimsy can become focal if they are the only things that stand out.

4a. Be First (Unilateral Innovation)

Make a visible, specific proposal before anyone else does. Even a mediocre proposal gains power from being the only proposal.

"The strongest argument in favor of R is the rhetorical question, 'If not R, what then?'"

Requirements for this to work:

  • The proposal must be visible to all parties
  • It must be specific (not vague)
  • It must remain unchallenged long enough to acquire default status

4b. Use a Mediator or Third Party

Recruit someone respected by all parties to make a "dramatic suggestion." The suggestion fills the vacuum of indeterminacy.

The mediator's power comes not from the quality of the suggestion but from the fact that it exists. A traffic cop at a jammed intersection helps even the drivers most disadvantaged by the routing.

4c. Frame the Problem

Reformulate the situation to make a favorable outcome appear as the "obvious" choice:

  • Choose which data to present (income figures → proportional split)
  • Choose which precedents to invoke
  • Choose which analogies to draw
  • Name the problem in a way that implies the answer

4d. Introduce Noise (Defensive)

If the existing focal point is unfavorable, flood the situation with additional variables until the old signal is drowned out and parties retreat to a simpler default (often 50-50).

4e. Find a Qualitative Boundary

Replace "how much?" questions with "which category?" questions. Continuous variables have no focal point. Discrete categories do.

  • Bad: "How much budget should marketing get?" (any percentage is defensible)
  • Good: "Should marketing own the launch budget, yes or no?" (binary = focal)
  • Bad: "How many weapons are acceptable?" (any number is debatable)
  • Good: "Nuclear or conventional?" (bright line = focal)

4f. Act, Don't Talk (Moves as Signals)

In strategic conflict, actions authenticate intentions more than words. Incur a visible cost or risk to make a proposal credible. A team that migrates its codebase to a new framework before the "standards meeting" has created a focal point through action, not argument.

4g. Leverage Irrelevant Alternatives

An option that is not even available can still magnetize expectations. The "shadow" of a 50-50 split coordinates expectations even when the rules make an exact 50-50 impossible. When proposing a focal point, reference a familiar benchmark even if it cannot be achieved exactly — it pulls the final answer toward it.

Step 5: Stress-Test the Focal Point

Before presenting the proposed focal point, verify it passes these tests:

  1. The "If Not Here, Where?" Test: If this focal point is rejected, is there an equally obvious alternative? If yes, it is too weak.
  2. The Newcomer Test: Would someone unfamiliar with the negotiation history arrive at the same answer from the situation alone?
  3. The Breach Test: If someone violates this focal point, would everyone notice? If the violation is ambiguous, the focal point is not crisp enough.
  4. The Concession Test: Can this focal point survive small adjustments? (Focal points that depend on exact numbers like 50% collapse if compromised to 47%. This is a feature, not a bug — it makes them harder to erode.)
  5. The Stability Test: Once established, does this focal point create a groove that makes future coordination easier?

Anti-Patterns — Check Output Against These

Before presenting a recommendation, verify it does not fall into these traps:

Optimizing instead of coordinating. The recommendation proposes the "best" answer instead of the most recognizable one. A territory split along the most equitable population line is objectively better than the river — but nobody can independently identify the same equitable line. The river wins because both sides can find it without talking.

Bad: "Divide the region by population density, giving each side roughly equal citizens." Good: "The river. It is the only line both sides will independently draw."

Proposing quantitative limits on a continuum. The recommendation suggests a specific number or percentage when a qualitative boundary exists. Nuance kills coordination — any number can slide to the next number.

Bad: "Limit chemical weapons to 50kg per engagement with monitoring provisions." Good: "No chemical weapons. Binary, unambiguous, no negotiation needed."

Offering multiple options. The recommendation presents 3 "equally good" alternatives and asks the user to choose. The entire purpose of a focal point is singularity — one answer that commands attention by having no competitor. Presenting options is the opposite of finding a focal point.

Bad: "Here are three viable pricing models: per-seat, per-action, or flat monthly." Good: "Per-seat monthly. It has the most precedent from adjacent SaaS. The others may be better, but this is the one everyone will independently guess."

Ignoring discrimination. The recommendation rejects a focal point because it is "unfair" to one party, when the cost of miscoordination is worse than the unfairness. Schelling: "beggars cannot be choosers about the source of their signal." A discriminatory focal point that coordinates is often better than a fair proposal that nobody can independently identify.

Bad: "The river disadvantages the eastern population, so we should find a more equitable line." Good: "The river disadvantages the east, but the 15 people who tried to draw a 'fairer' line produced 14 different answers. The river is the only line that works."

Step 6: Present Recommendation

Structure the output as:

## Focal Point Analysis

**Situation**: [One-sentence description of the coordination problem]
**Parties**: [Who must align]
**Stakes of Miscoordination**: [What happens if they fail to converge]

### Existing Focal Points
[List any found in Step 2 with strength ratings]

### Diagnosis
[If convergence is failing, why — from Step 3]

### Recommended Focal Point
[The specific proposal]

**Why this works**:
- [Which magnets it activates: uniqueness, simplicity, precedent, symmetry, cultural salience]
- [Why alternatives are weaker]

**How to establish it**:
- [Which technique from Step 4: be first, mediator, framing, noise, qualitative boundary]
- [Specific actions to take]

**Risks**:
- [What could undermine it]
- [What happens if it is breached]

**Stress Test Results**:
- If Not Here, Where? → [pass/fail]
- Newcomer Test → [pass/fail]
- Breach Test → [pass/fail]
- Concession Test → [pass/fail]
- Stability Test → [pass/fail]

Reference Material

For detailed source quotes, examples, and the full Schelling methodology, read references/schelling-focal-points.md.

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 Focal Point Finder AI skill do?

This skill should be used when someone needs to find, propose, or evaluate a focal point in a coordination, negotiation, or alignment problem. A focal point is a solution that people converge on without explicit agreement — because it is uniquely prominent, simple, or recognizable. Based on Thomas Schelling's "The Strategy of Conflict." Triggers on "where should we align?", "how do we get everyone on the same page?", "what's the obvious choice?", "find a focal point", "Schelling point", "coordination problem", "how do we agree without talking?", "what would everyone pick?", "propose a stand...

Why use Focal Point Finder on TypingMind?

Because you install it once and use it with any model. Focal Point Finder 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 Focal Point Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gnurio/nurijanian-skills/tree/main/skills/focal-point-finder. 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 Focal Point Finder?

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 Focal Point Finder?

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

Is the Focal Point Finder AI skill free?

Yes. It is published on GitHub by gnurio 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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