onboard
onboard is an Other agent platforms skill for AI agents, published by LonelyHerbivore in the Trellis-Herbivore repository on GitHub. Skillspace rates onboard D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Interactive three-part onboarding for new team members to the Trellis AI-assisted workflow system. Covers core philosophy (AI memory, project-specific knowledge, context drift), system structure and command deep-dives, real-world workflow examples, and guideline customization. Use when a new developer joins the project, someone needs to understand the Trellis workflow, or project guidelines need initial setup.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 90
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
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- AGPL-3.0
- Adoption
- Adopted by 8 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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