sdcpn-modelling
sdcpn-modelling is a Process documentation & SOPs skill for AI agents, published by hashintel in the hash repository on GitHub. Skillspace rates sdcpn-modelling D (68/100) and it passed the safety scan; a judge model has also reviewed it.
Elicit or revise an operational process model, maintain its recoverable workpiece, and construct a checked SDCPN when Petrinaut capabilities are available. Use for a process-modelling interview, Petri net, or analysis or revision of either artifact.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 1,655
Placed #4 of 6 in the judged category final for Process documentation & SOPs.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
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
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #4 of 6 in the judged category final for Process documentation & SOPs.
- Trigger
55 55 - Instructions
42 42 - Specificity
62 62 - Safety
78 78 - Disclosure
58 58 - Maintenance
48 48
Careful workpiece-versioning and honesty-about-attribution discipline is buried under dense, self-referential jargon that makes the actual steps hard to follow.
Not checked yet
- 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.