forming-an-openrig-mental-model
forming-an-openrig-mental-model is a Codebase mapping & onboarding skill for AI agents, published by mvschwarz in the openrig repository on GitHub. Skillspace rates forming-an-openrig-mental-model F (53/100) and it passed the safety scan; the rating is based on static analysis only.
Use when an agent is newly oriented to OpenRig and needs to form an accurate mental model of the system fast — what rigs are, how skills load, what the topology shapes mean, what the product loop is. For agents booting into a new seat or returning to OpenRig work after time away. NOT for HA-pair compaction recovery (that's the pair-of-seats coordination pattern; orientation is a solo task) or for specific operational procedures.
- Grade
- F
- Quality
- 53 / 100
- Safety
- Passed
- GitHub stars
- 53
Unproven: rated by static analysis only, not yet compared head-to-head.
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
- 80 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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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