A Chinese-language interview-question guide for roles focused on AI-agent development. It covers agent design, language-model calls, tool integration, MCP, retrieval-augmented generation, context management, and multiple agents working together.
A skill for creating interview questions about Alibaba backend engineering. The description focuses on business depth, real project delivery, and choosing middleware for complex situations.
Use when the user mentions Nubase broadly, wants a backend for an AI-generated app, or needs to deploy/publish generated code online — across Database, Auth, Storage, Assets (static frontend CDN), Functions (edge/serverless), AI Gateway, Memory, cron/scheduled jobs, Supabase-style REST/RLS, servicerole keys, or MCP.…
Admin and maintenance workflows for Ogham shared memory. Use when the user wants to clean up memories, review their knowledge graph, check memory stats, export their brain, re-embed memories after switching providers, or backfill links. Triggers on "clean up my memory", "memory stats", "how many memories", "export my…
Smart retrieval from Ogham shared memory. Use when the user wants to recall what they know, find related context, bootstrap session context, or explore their knowledge graph. Triggers on "what do I know about", "find related", "search ogham", "search memory", "recall", "context for this project", "what did we decide…
Structured memory capture for Ogham shared memory. Use when the user wants to store findings, remember something, save what was learned, or capture a decision. Triggers on "remember this", "store this", "save this finding", "save what we learned", "capture this decision", "log this", or any request to persist…
Use when the GM asks to update, extend, or fix the Campaign Chronicle (CampaignChronicle.md) from PlayerNotes. Triggers on requests to add a session to the chronicle, summarize player notes into the campaign record, or fix missing details in existing chronicle entries. The core discipline is preserving precise…
Use when the GM wants to prepare a new RPG session — creating a session folder, main prep file, and scene sub-files in the Obsidian vault. Triggers on requests to prep, plan, or create a new session, or to build encounters and scenes using the 5 Room Dungeon or Situations frameworks.
Use when you need to find, list, or read-and-summarize Obsidian vault notes mechanically — e.g., "find all NPC notes tied to faction X", "list all session N scene files", "read frontmatter of these 12 notes and return a table", "grep all Locations/ notes for wikilinks to [[NPC Name]]". Dispatches a Haiku subagent to…
Select and connect the right vector-store backend for the vector-mcp MCP server — chromadb, postgres/pgvector, qdrant, couchbase, or mongodb — and supply the correct dbtype/connection parameters that every collection and search call needs. Use when the agent must decide which engine to target, wire up…
Create, populate, list, and delete vector-store collections through the vector-mcp MCP server's vectorcollectionmanagement tool. Use when the agent must stand up a new RAG collection, ingest documents (from a directory, file paths/URLs, or raw text) into an existing collection, enumerate collections, or drop one …
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis with two-column tables. Left column preserves the chapter content; right column maps every idea to the reader's actual life using brain context. Output is a single brain page at media/books/ -personalized plus an optional PDF via brain-pdf.
Day-one data bootstrapping for a new brain. Sequences the highest-leverage data sources to go from empty brain to useful brain in one session. Uses the agent host's managed connectors for safe credential handling — the agent never holds raw API keys. Covers Gmail import, calendar sync, contacts seeding, X/Twitter…
Soup.net is connected. Call getbriefing once per session for the canonical recipe format, role/voice patterns, when-to-check guidance, the user's recipe books, and a corpus sample — that's the source of truth. This skill is a pointer only; everything substantive lives in the briefing.
A reference for using weasley-deepmind, a server that stores and retrieves an AI agent’s long-term memories between sessions. It describes memory storage, search, language processing, and related tools.
A persistent memory service for AI coding assistants, storing project rules, architecture decisions, bug fixes, and other knowledge across sessions. It uses a database to search stored information by meaning.
Edit this project's Railway infrastructure-as-code configuration. Use this skill whenever the user asks to create, change, import, review, or troubleshoot Railway project infrastructure for the current repository, including services, databases, buckets, custom domains, replicas/regions, groups, environment variables…