Last updated: 2026-09-10.
AI Engineering is a library of Markdown skill packages, guide material, support templates, and protocol distributions for LLM coding assistants. It is built around a simple split:
docs/explains the repository for human readers.knowledge/stores the source and derived material consumed by skills and packages.protocols/stores protocol distributions such as CCDP.
- Repository overview
- Skill library
- Collaboration framework
- Knowledge library anatomy
- Building and installing
- Protocols
- Contributing
- Origins
The repository currently includes:
- domain/tooling skill packages for Rust, Go, Erlang/OTP, C++, JavaScript/Deno, Cobalt, Tailwind CSS, Visual Design, Biome, and Deno lint;
- the
scientific-methodsmethod skill for practical inquiry, controlled comparison, experiment planning, evaluation rubrics, evidence capture, and regression analysis; - the
document-extractionmethod skill for preparing PDF, EPUB, HTML, and converted-source inputs with structure, media, locator, manifest, readiness, and caveat records; - the
concept-cardsmethod skill for provenance-bearing concept-card extraction, validation, verification, reconciliation, relationships, competency questions, and memory-admission decisions; - the
collaboration-frameworkcomposite framework/operational skill, with its framework material underknowledge/; - reusable support material such as the
templates/GUIDE.mdsupport template; - the Composite Cognition Dispatch Protocol under
protocols/ccdp/.
For implementation handoffs, engineering-methods provides From Slice to Implementation Prompt and a CC prompt template, available standalone and through collaboration-framework.
make help # list package, validation, and install targets
make all # build all installable skill zips into target/skills/
make collab-framework # build target/skills/collaboration-framework.zip
make document-extraction # build target/skills/document-extraction.zip
make concept-cards # build target/skills/concept-cards.zip
make print-skill-zips # list release-uploadable skill zip paths
make check-skills # validate SKILL.md descriptions
make check-skill-versions # validate source and generated skill versions
make audit-skills # measure source descriptions and aggregate pressure
make audit-live-skills # measure descriptions actually rendered by Codex
make test-skill-tools # verify parsing and per-file approval behavior
make check-package-paths
make install # install built skills into ~/.agents/skillsSkill checks require Python and PyYAML. See Skill Description Maintenance for setup, installed-catalog evaluation, and LLM shortening proposals with per-file approval.
CCDP is packaged separately from installable skills:
make ccdp
make ccdp-package
make check-ccdp-packageai-engineering/
├── README.md # repository orientation
├── Makefile # package, validation, install, and CCDP targets
├── docs/ # end-user repository documentation
├── knowledge/ # skill source and derived knowledge substrate
├── protocols/ # protocol distributions, including CCDP
├── templates/ # cross-cutting templates, including GUIDE.md
├── scripts/ # package and validation helpers
└── assets/ # README images and other public assets
The docs/ guides are explanatory wrappers. They should help readers choose,
install, build, and contribute without duplicating the full material under
knowledge/.
Skill kind and topology are separate. Kind says what a skill is about, such as domain/tooling, framework/operational, or method work. Topology says how a skill composes: an atomic skill is loaded for one clear, self-contained purpose, while a composite skill selects, sequences, routes, governs, composes, etc., multiple loadable components.
The rust skill is an example of an atomic domain/tooling skill. Whereas
collaboration-framework is a composite
framework/operational skill and remains the daily-driver composer for most users of the ai-engineering repo. To clear up an additional conceptual point, protocols (such as CCDP) are RFC-style documents, not installable skill packages.
MIT - see LICENSE.
Individual knowledge bases synthesize material from sources under various licenses, documented inside each skill's own source materials. When in doubt, defer to the original sources.
