onboard

Solid

Quick protocol recommendation from recent sessions, or quest-based learning through scenario, trial, and quiz.

AI & Automation 125 stars 11 forks Updated today MIT

Install

View on GitHub

Quality Score: 81/100

Stars 20%
70
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Onboard Skill Start with a quick recommendation based on recent sessions, then optionally continue to guided learning — so users experience value first, learn second. Invoke directly with `/onboard` when the user wants onboarding or protocol discovery. ## When to Use Invoke this skill when: - A new user wants to discover which epistemic protocols fit their workflow - A user wants to experience protocols through guided practice - Re-onboarding after new protocols are added or workflow changes Skip when: - User wants analytical report with evidence and HTML artifact (use `/report`) - User already knows which protocol to use (direct invocation) - Quick single-protocol question (answer directly) ## Workflow Overview ``` Quick Proof: ENTRY → QUICKSCAN → PICK-1 → EVIDENCE → TRIAL → INSIGHT → NEXT Targeted: ENTRY → QUICKSCAN → MAP → SCENARIO → TRIAL → QUIZ → GUIDE Targeted + std: ENTRY → SCENARIO → TRIAL → QUIZ → GUIDE ``` | Phase | Owner | Tool | Purpose | |-------|-------|------|---------| | 0. Entry | Main | Gate | Path selection: quick/targeted | | 1. Quick Scan | Main | Glob, Read | User Context Profile extraction | | 2a. Pick-1 | Main | — | Quick path: select 1 recommendation | | 2b. Evidence | Main | — | Quick path: show 1 evidence card | | 2. Map | Main | — | Targeted path: Profile → Protocol matching | | 3. Scenario | Main | Gate | Targeted path: context-personalized intervention point | | 4. Trial | Main | Gate | Real protocol execution (quick: mini tria...

Details

Author
jongwony
Repository
jongwony/epistemic-protocols
Created
7 months ago
Last Updated
today
Language
JavaScript
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category