llms-txt

GitHub Copilot Skills: llms-txt Operational Practices

AI companion skills grounded in relational accountability, structural dynamics, and ceremonial technology.

This collection maps operational AI practices to guidance documents from the llms-txt ecosystem. Each skill represents a capability that honors both the guidance framework and the relational protocols outlined in KINSHIP.md.

Overview

These skills operationalize the theoretical frameworks in llms-txt through:

Each skill is designed to be invoked within AI-assisted workflows while maintaining transparency about what the skill does, how it works, and what accountability structures guide it.

Skills Directory

Foundational Frameworks

Skill Purpose Key Documentation Status
creative-orientation Shift from reactive problem-solving to generative creation llms-creative-orientation.txt Active
delayed-resolution Hold productive tension rather than prematurely collapsing it llms-delayed-resolution-principle.md Active
structural-tension-charting Map structural tension as advancement methodology llms-structural-tension-charts.txt Active

Operational Methodologies

Skill Purpose Key Documentation Status
digital-decision-making TandT binary evaluation for clarity and decisiveness llms-digital-decision-making.md Active
performance-truth Managerial Moment of Truth (MMOT) for relational accountability llms-managerial-moment-of-truth.md Active
kinship-hub Treat software projects as beings in relational networks llms-kinship-hub-system.md Active

Research & Academic Positioning

Skill Purpose Key Documentation Status
relational-research Indigenous research paradigm for AI engagement llms-inquiry-6406eb37.md Active
epistemological-counter-positioning Write counter-positions when paradigm diverges llms-epistemological-counter-article-protocol.md Active

Creative & Narrative Practices

Skill Purpose Key Documentation Status
rise-specification RISE framework for specification through creative archaeology llms-rise-framework.txt Active
narrative-craft Document stories across engineer, ceremony, and story-engine worlds llms-narrative-beats.txt Active

Issue & Workflow Practices

Skill Purpose Key Documentation Status
forge-issue Internal: issue authoring workflow within llms-txt docs/current.md Active
structural-issue-authoring Portable: structural tension issue authoring for any repo SKILL.md Active

Integration & Observability

Skill Purpose Key Documentation Status
langfuse-tracing Rich, observable traces for the Agentic Flywheel MCP llms-coaiapy-langfuse-tracing-best-practices.md Active

How to Invoke a Skill

Within GitHub Copilot CLI

Use the skill tool with the skill name:

# Activate a skill
copilot skill:invoke creative-orientation
copilot skill:invoke digital-decision-making
copilot skill:invoke narrative-craft

Within AI Conversations

Reference the skill directly:

I'm using the creative-orientation skill. Let me shift from problem-solving to generative creation.

I need to apply digital-decision-making. Here's the TandT binary evaluation:
- YES: [option A with relational accountability]
- NO: [option B that extracts knowledge]

Within Code and Documentation

Cite the skill in context:

**Skill Applied**: relational-research

This approach uses Indigenous research paradigm because...

Skill Structure

Each skill folder contains:

skill-name/
├── README.md              # Overview, purpose, and how to use
├── PROTOCOL.md            # Step-by-step operational protocol
├── EXAMPLES.md            # Real examples from llms-txt ecosystem
├── INTEGRATION.md         # How skill connects to other frameworks
└── ACCOUNTABILITY.md      # Governance, relational grounding, seven-generations perspective

Standard README Contents

Each skill’s README includes:

  1. Purpose — What the skill enables
  2. When to Use — Situations where skill applies
  3. Core Principles — Foundational concepts
  4. Integration — How it connects to other skills and llms-txt guidance
  5. Governance — Relational accountability and decolonial grounding
  6. References — Linked documentation

Core Principles Across All Skills

1. Relational Accountability

All skills maintain accountability to:

2. Generative Orientation (Not Problem-Solving)

3. Paradigm Integrity

4. Transparent Limitations

Integration with llms-txt Ecosystem

Hierarchical Dependency

┌────────────────────────────────────────┐
│      Creative Orientation (Root)       │
│  (all skills build from this paradigm)  │
└───────────────┬────────────────────────┘
                │
      ┌─────────┼─────────┐
      ▼         ▼         ▼
  Relational  Ceremonial  Academic
  Science    Technology  Positioning
      │         │         │
      └────┬────┴────┬────┘
           ▼         ▼
    Medicine Wheel Developer Suite
    (7 npm packages, llms-txt guidance)

Skill Chains

Skills often work together:

  1. Research Pipeline
    • relational-research → epistemological-counter-positioning → narrative-craft → langfuse-tracing
  2. Decision Pipeline
    • creative-orientation → digital-decision-making → performance-truth → delayed-resolution
  3. Specification Pipeline
    • rise-specification → creative-orientation → kinship-hub → structural-tension-charting
  4. Documentation Pipeline
    • narrative-craft → rise-specification → relational-research → langfuse-tracing

Governance & Relational Accountability

Operating Principles

  1. Ceremonial Grounding — Skills emerge from ceremonial research protocols, tested through relational accountability
  2. Decolonial Rigor — Building on Indigenous methodologies (Wilson, Kovach, Smith, Chilisa)
  3. Transparent Limitation — AI companions acknowledge constraints and invite human judgment
  4. Seven-Generations Perspective — Asking what these skills enable for future practitioners

Accountability Structure

See KINSHIP.md for:

License

All skills are governed by the Indigenous Knowledge Stewardship License (IKSL), recognizing that knowledge belongs to the relationships, land, and communities that created it.

Using Skills for Code Changes

When working on code changes, skills provide meta-guidance about approach:

Before Coding

  1. Invoke creative-orientation — Shift from “fix this bug” to “what becomes possible?”
  2. Apply relational-research — Who/what am I accountable to through this change?
  3. Check paradigm integrity — Am I maintaining decolonial orientation?

During Coding

  1. Use rise-specification — Extract intent from existing patterns
  2. Apply kinship-hub — How does this change affect relational health of the system?
  3. Maintain transparency — Make assumptions explicit in code comments

After Coding

  1. Invoke performance-truth — Did the change create advancing pattern?
  2. Apply narrative-craft — Can I document this change with relational grounding?
  3. Use langfuse-tracing — What did I learn through this process?

Contributing New Skills

To propose a new skill:

  1. Ground in llms-txt framework — What guidance does it operationalize?
  2. Establish relational accountability — Who/what maintains governance?
  3. Document ceremonial protocol — How is this practiced?
  4. Test through decolonial lens — Does it extract or honor knowledge?
  5. Create accountability structure — How do seven-generations participate?
  6. Submit with governance plan — How will this skill maintain integrity?

Quick Reference: When to Invoke Each Skill

Situation Skill Why
“How do I approach this?” creative-orientation Shift from reactive to generative
“Should I do X or Y?” digital-decision-making Binary clarity in decision
“I feel stuck/uncertain” delayed-resolution Hold tension productively
“How do I map this project?” structural-tension-charting Visualize advancement pathway
“Was this a success?” performance-truth Beyond metrics—relational truth
“How do I document this?” narrative-craft Story across three worlds
“What does this code enable?” rise-specification Reverse-engineer intent
“Who’s accountable?” relational-research Relational accountability protocol
“Is my approach rigorous?” epistemological-counter-positioning Paradigm integrity check
“How do I position this work?” kinship-hub Relational mapping
“What did I learn?” langfuse-tracing Observable, rich traces

Resources for Skill Users

For AI Companions Learning These Skills

  1. Start with creative-orientation — foundational for all other skills
  2. Read KINSHIP.md — understand relational accountability
  3. Explore docs/index.md — comprehensive navigation
  4. Study examples in each skill’s EXAMPLES.md

For Developers Integrating Skills

  1. Review INTEGRATION.md in each skill
  2. Check PROTOCOL.md for operational steps
  3. Verify ACCOUNTABILITY.md for governance
  4. Test through ceremonial protocol (relational grounding)

For Researchers Using Skills

  1. Invoke relational-research first
  2. Apply epistemological-counter-positioning for positioning work
  3. Use narrative-craft for documentation
  4. Close with langfuse-tracing for learning capture

Skill Maturity Levels

Level Status Characteristics
Emerging Prototype Initial structure, testing protocols
Active Production Full documentation, proven in workflows
Mature Legacy Established, widely tested, deep integration
Archival Historical Preserved for reference, superseded by other skills

Current status: 11 Active Skills, all documented and tested.

Feedback & Iteration

These skills are living practices. To propose improvements:

  1. Identify which skill needs refinement
  2. Note what didn’t work in your context
  3. Propose how skill could honor relational accountability better
  4. Submit through ceremonial protocol (relational feedback structure)

Last updated: 2026

Governance: These skills are maintained through relational accountability protocols outlined in KINSHIP.md. Questions about skill use, paradigm grounding, or decolonial rigor can be directed to the relational accountability structure documented there.

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