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Behavior Design

Community
Mark393295827
behavior-design

Use when a goal must be converted into a repeatable behavior, cue, SOP, review cadence, and identity-aligned reinforcement.

Overview

PublisherMark393295827
Repositorythird-brain-v7-skills
Skill namebehavior-design
Stars
141
Forks
22
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 Mark393295827 on GitHub. Read the source before you install it.

Installation

Install the Behavior Design 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/Mark393295827/third-brain-v7-skills/tree/main/skills/behavior-design
  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/Mark393295827/third-brain-v7-skills.git /tmp/third-brain-v7-skills
mkdir -p .claude/skills
cp -r /tmp/third-brain-v7-skills/skills/behavior-design .claude/skills/behavior-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Behavior Design 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 Behavior Design 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 Behavior Design 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.

Behavior Design

<skill_contract> Actor, desired outcome, current behavior, context, constraints, baseline evidence, and review horizon. An agency-preserving HAS behavior system with cues, effort levels, SOP, measures, recovery, and review cadence. The target behavior is observable, runnable on a low-motivation day, evidenced, and assigned one review owner. <non_goals>Coercion, unsupported identity claims, vague motivation advice, or optimizing lagging outcomes without behaviors.</non_goals>

Convert an outcome into the smallest observable behavior system that can survive low-motivation days. Preserve agency; optimize the environment before blaming the actor.

Usage Template

Provide: desired outcome, actor, context, current behavior, constraints, review horizon, and available evidence. Optional: failed attempts and environmental cues.

Workflow

  1. Restate the outcome as an observable change, not an identity label.
  2. Establish baseline frequency, friction, trigger context, and hard constraints.
  3. Separate controllable behavior from lagging outcome.
  4. Set one review horizon and one owner.

<unknowns_gate>

Classify unknowns as known, probeable, testable, or blocked. If actor, target behavior, or safety boundary is absent, return NEEDS_INPUT with one minimal question. A reversible assumption is allowed only when labeled and paired with a same-cycle test.

</unknowns_gate>

Build the HAS sequence:

  1. H1 Goal: translate the outcome into one leading behavior and one lagging measure.
  2. H2 Habit: define anchor, cue, location, and three effort levels: minimum (about 2 minutes), normal, and stretch.
  3. H3 SOP: write trigger -> action -> evidence -> recovery -> stop so a missed run has a next move.
  4. H4 Review: select a cadence; compare planned versus observed behavior and change one variable only.
  5. H5 Identity: use evidence-based reinforcement: “I am becoming X because I repeatedly did Y,” never unsupported affirmation.

Reduce friction before adding motivation. Prefer defaults, visible cues, prepared tools, and short feedback latency. Keep the minimum behavior useful rather than ceremonial.

Check that the behavior is observable, starts in a named context, fits the minimum effort budget, produces evidence, and has a recovery path. Reject plans that depend on constant willpower, hide coercion, or measure only outcomes. If the check fails, revise the highest-friction element once and re-evaluate.

<state_contract>

Persist {run_id, status, attempt, budget, evidence, unknowns, last_error, next_action} plus baseline, current H1-H5 design, review date, and revision history. Update atomically after each review; never overwrite prior observations.

</state_contract>

Failure Protocol

  • NEEDS_INPUT: a target, actor, or boundary is missing; ask one narrow probe.
  • INSUFFICIENT_EVIDENCE: baseline is unknown; run a short observation period before optimizing.
  • VERIFY_FAILED: the behavior is not observable, feasible, or linked to the outcome; revise one variable.
  • BUDGET_STOP: the review horizon or effort budget is exhausted; preserve state and report the next experiment.

Output Contract

Return status, result (H1-H5 plan), evidence (baseline and measures), unknowns, and next_action (owner plus review date).

Edge Cases

  • Motivation is near zero: keep the cue and reduce the action to a useful minimum; do not expand the reward system.
  • Repeated misses occur despite compliance: treat the goal-behavior link as unverified and test a different leading behavior.

Success Metrics

  • One named cue reliably starts one observable minimum behavior.
  • Execution evidence is captured at the chosen cadence.
  • Reviews change the system using observed friction, not self-judgment.

Quality Gates

  • Outcome, leading behavior, and lagging measure are distinct.
  • Minimum action, recovery path, owner, and review date exist.
  • The design preserves agency and has no coercive mechanism.
  • Completion claims use observed behavior evidence.

</skill_contract>

Frequently asked questions

What does the Behavior Design AI skill do?

Use when a goal must be converted into a repeatable behavior, cue, SOP, review cadence, and identity-aligned reinforcement.

Why use Behavior Design on TypingMind?

Because you install it once and use it with any model. Behavior Design 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 Behavior Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/behavior-design. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Behavior Design?

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 Behavior Design?

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

Is the Behavior Design AI skill free?

Yes. It is published on GitHub by Mark393295827 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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