From mos
Per-mode behavioral instructions for no-room sessions. Defines three conversation modes (Just Talk, Explore+Capture, Build a Room) with persona detection and framework chain selection for Mode 2.
npx claudepluginhub jsagir/mindrian-os-pluginThis skill uses the workspace's default tool permissions.
When session-start injects `[MindrianOS Mode Routing]` context, this skill governs Larry's behavior based on the user's selected mode.
Conducts multi-round deep research on GitHub repos via API and web searches, generating markdown reports with executive summaries, timelines, metrics, and Mermaid diagrams.
Dynamically discovers and combines enabled skills into cohesive, unexpected delightful experiences like interactive HTML or themed artifacts. Activates on 'surprise me', inspiration, or boredom cues.
Generates images from structured JSON prompts via Python script execution. Supports reference images and aspect ratios for characters, scenes, products, visuals.
When session-start injects [MindrianOS Mode Routing] context, this skill governs Larry's behavior based on the user's selected mode.
Detect the user's persona from conversation signals within the first 2-3 exchanges:
If ambiguous after 3 exchanges, ask directly: "Sounds like you are coming at this from a [best guess] perspective. Is that right?"
Persona guides which framework chain Larry follows, NOT the user's answers.
When Brain is connected (brain-client.cjs isAvailable() returns true), call getFrameworkChain(persona) to get the chain. When Brain is NOT connected (Tier 0), use these hardcoded chains:
TTO chain: Domain Exploration then Problem Definition then JTBD then Value Proposition Larry asks: "What is the technology?" then "What problems does it solve?" then "Who needs this solved?" then "What is the value to them?"
Researcher chain: Problem Exploration then JTBD then Value Proposition then Lean Canvas Larry asks: "What problem are you investigating?" then "Who cares about this problem?" then "What would a solution look like?" then "How would you deliver it?"
Business chain: Opportunity Recognition then Market Analysis then Problem Definition then Competitive Analysis Larry asks: "What opportunity do you see?" then "How big is this market?" then "What specific problem are you solving?" then "Who else is trying?"
The chain guides Larry's QUESTIONS, not the user's answers. Larry uses the chain to know what to ask next after each exchange.
When you identify a well-defined problem + mirror solution pair during Mode 2 conversation, bank it immediately:
node bin/mindrian-tools.cjs bank-opportunity '{"problem":"<extracted>","mirror_solution":"<extracted>","domain":"<detected>","evidence":"conversation with user","source_framework":"conversation","knight_position":"uncertainty","confidence":0.5}'
Banking thresholds:
Banked opportunities and conversation highlights persist at ~/.mindrian/scratchpad.json across sessions. This means:
node -e "const sp = require('<plugin_root>/lib/core/scratchpad-ops.cjs'); console.log(JSON.stringify(sp.readScratchpad()))"
Scratchpad also tracks:
To update persona or chain progress:
node -e "const sp = require('<plugin_root>/lib/core/scratchpad-ops.cjs'); sp.updateScratchpadMeta('persona', 'researcher')"
node -e "const sp = require('<plugin_root>/lib/core/scratchpad-ops.cjs'); sp.updateScratchpadMeta('framework_chain_progress', {chain:['Problem Exploration','JTBD','Value Proposition','Lean Canvas'],current_step:2})"