Concept Graph

Concept Graph is an AI Engineering skill for Claude Code, published by WILLOSCAR in research-units-pipeline-skills.

499 stars39 forkson WILLOSCAR/research-units-pipeline-skillsAdded 2026/08/26Repository updated 2026/08/26

claudeclaude-codecodexgptpipelineresearchresearch-paperresearch-projectresearch-toolskillstoolsunitsvibevibe-codingvibecoding

Install in seconds

Install Concept Graph

Copy Concept Graph into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/concept-graph ~/.claude/skills/concept-graph

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/WILLOSCAR/research-units-pipeline-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: .codex/skills/concept-graph/SKILL.md in WILLOSCAR/research-units-pipeline-skills
Installs to: ~/.claude/skills/concept-graph
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Concept Graph does

Concept Graph builds a deterministic prerequisite DAG from an approved tutorial spec and writes it to outline/concept_graph.yml. Use it when tutorial concepts need stable ordering before module planning.

Concept Graph is cataloged under AI Engineering on DirSkills. Concept Graph comes from a repository tagged claude, claude-code, codex, gpt and pipeline.

Documentation

README

From the original repository

Concept Graph

Materializes the tutorial spec's structured concept inventory into outline/concept_graph.yml.

Input

output/TUTORIAL_SPEC.md

Output

outline/concept_graph.yml

Contract

The graph must contain:

nodes: {id, title, summary, source_ids, objective_refs}
edges: {from, to} meaning prerequisite order

Script boundary

scripts/run.py should:

load structured spec data
emit stable node ids and prerequisite edges
fail if the result would be cyclic or empty

Do not duplicate spec-parsing heuristics in multiple places; keep them in shared tutorial tooling.

Acceptance

outline/concept_graph.yml exists
all nodes have stable ids
the graph is a DAG

Non-goals

module clustering
exercise generation
tutorial prose

Frequently asked about Concept Graph

What else does WILLOSCAR publish alongside Concept Graph?
Concept Graph is one of 25 skills that DirSkills catalogs from WILLOSCAR/research-units-pipeline-skills, the repository it ships in. Its siblings there include Agent Survey Corpus, Anchor Sheet and Appendix Table Writer. Each one is a separate skill with its own page in this directory, installs the same way Concept Graph does, and is maintained by WILLOSCAR in that same repository. The rest of the collection is listed on the WILLOSCAR/research-units-pipeline-skills page.
How does Concept Graph compare to other AI Engineering skills?
Concept Graph ranks #2176 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Concept Graph against them. Open each page to compare what they document and how they install.