Cognitive Core Skills

Cognitive core skills are the mental operating capabilities an LLM or AI Agent needs to move from chat response to useful digital co-worker. An LLM predicts and generates language. An AI Agent wraps that LLM with memory, planning, tools, integrations, verification, and action control so it can pursue goals inside real workflows.

Cognitive core skills are the agent operating brain: perception to know the situation, memory to preserve continuity, reasoning to judge, planning to sequence work, action selection to execute, verification to confirm progress, learning to improve, and governance to stay safe.

Repository overview

This repository contains a universal, industry-neutral taxonomy package for:

• LLM capabilities
• SLM capabilities
• AI agent capabilities
• World model capabilities
• Text-based cognitive skills
• Human-action cognitive skills
• Persistent LLM Wiki knowledge operations
• OKF-style knowledge cataloging operations

Why star or fork this project

• Practical: ready-to-use taxonomy data, schemas, and validation tests.
• Operational: includes human-action skills and governance-oriented constructs.
• Reusable: JSON, YAML, and markdown skill cards for easy integration.
• Collaborative: contribution templates, roadmap, and CI in place.

Quickstart

1. Read the taxonomy package docs in docs/cognitive-core-skills/.
2. Explore machine-readable data in data/.
3. Browse generated skill cards in Skills/index.md.
4. Run validation locally.

Current status

• Taxonomy version: 1.0.0
• Skill count: 159
• Domains covered: 13
• Generated skill files in Skills/: 159 skill cards plus Skills/index.md
• CI enabled for taxonomy and benchmark fixture tests

Capability model differences

System type	Primary strength	Typical limitation without augmentation
LLM	Broad language understanding, synthesis, reasoning, drafting	Weak continuity and no autonomous bounded action by default
SLM	Low-latency, low-cost, private, constrained inference	Narrower transfer and lower open-domain depth
AI Agent	Goal pursuit across memory, planning, tools, and actions	Requires robust verification, control gates, and oversight
World Model	State and dynamics modeling, simulation, forecasting	Requires grounded observations and updated environment state

Key package paths

Documentation:

• docs/cognitive-core-skills/README.md
• docs/cognitive-core-skills/taxonomy.md
• docs/cognitive-core-skills/text-based-skills.md
• docs/cognitive-core-skills/human-action-skills.md
• docs/cognitive-core-skills/world-model-skills.md
• docs/cognitive-core-skills/llm-wiki-skills.md
• docs/cognitive-core-skills/okf-skills.md
• docs/cognitive-core-skills/evaluation-rubric.md
• docs/cognitive-core-skills/cognitive-debt-index.md
• docs/cognitive-core-skills/glossary.md
• docs/cognitive-core-skills/CHANGELOG.md

Machine-readable artifacts:

• data/cognitive-core-skills.json
• data/cognitive-core-skills.yaml
• schemas/cognitive-core-skill.schema.json
• schemas/cognitive-core-taxonomy.schema.json

Benchmarks and examples:

• benchmarks/rubric-task-traces.json
• examples/cognitive-core-skill-card.md
• examples/agent-skill-assessment.md

Generated skills directory:

• Skills/index.md
• Skills/<skill_id>.md (one file per taxonomy skill)

Tests and CI:

• tests/test_cognitive_core_taxonomy.py
• tests/test_rubric_benchmark_fixtures.py
• .github/workflows/taxonomy-ci.yml

Community and project health:

• CONTRIBUTING.md
• GOOD_FIRST_ISSUE_GUIDE.md
• RELEASE_CHECKLIST.md
• ROADMAP.md
• .github/ISSUE_TEMPLATE/bug_report.yml
• .github/ISSUE_TEMPLATE/feature_request.yml
• .github/pull_request_template.md

Recent taxonomy update

Added human-action skill:

• ha_consequence_understanding - Human-Action Consequence Understanding

Purpose: understand likely downstream operational, compliance, and workflow consequences before executing human-action tokens.

Added planning skill:

• plan_long_horizon_skill - Long-Horizon Skill

Purpose: maintain coherent long-horizon execution across milestones, dependencies, and replanning triggers.

Run validation locally

py -m pytest tests/test_cognitive_core_taxonomy.py tests/test_rubric_benchmark_fixtures.py -q

How to add a new skill

1. Add the skill card to data/cognitive-core-skills.json.
2. Mirror the same skill in data/cognitive-core-skills.yaml.
3. Ensure unique id and unique name.
4. Add valid related_skills references.
5. Regenerate the Skills/ folder markdown cards from taxonomy data.
6. Update docs/cognitive-core-skills/CHANGELOG.md under Unreleased.
7. Run the local pytest command above.

Regenerate skill markdown files

When taxonomy data changes, regenerate skill card markdown files in Skills/ so they remain synchronized with data/cognitive-core-skills.json.

Expected result:

• one markdown file per skill id
• one generated index file at Skills/index.md

Run:

py scripts/generate_skills.py

Attribution and license boundaries

This taxonomy package adapts high-level architecture/documentation patterns from:

• third-party/autoresearch-master
• third-party/knowledge-catalog-main
• third-party/knowledge-catalog-main/okf

No third-party source code is copied into taxonomy artifacts.

Star history

If this taxonomy is useful to you, a star helps others discover it and tells us which direction to invest in next.

Support this project

• Star the repo to bookmark it and help with discoverability.
• Fork the repo if you want to adapt the taxonomy, schemas, or skill cards for your own agent stack.
• Open an issue for a missing skill, a schema question, or a benchmark idea. See GOOD_FIRST_ISSUE_GUIDE.md for beginner-friendly entry points.
• Share a "Show and tell" write-up if you build something on top of this taxonomy once Discussions are enabled.