def-graph
def-graph is a Model training & evaluation skill for AI agents, published by ShenShan123 in the r2g-skills repository on GitHub. Skillspace rates def-graph B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Convert clean, signed-off physical-design files (DEF/LEF/liberty/SPEF from an ORFS backend run) into training-ready PyTorch-Geometric graph datasets. Use when the user wants to build a graph dataset from placed-and-routed designs — the five graph views (b–f), the tech-lib/LEF/DEF parser, node/edge feature extraction, or per-cell/per-net labels (congestion, RC parasitics, wirelength, timing, IR drop). Companion to the signoff-loop skill, which produces the physical-design inputs this skill consumes.
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 41
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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