Loading...
Loading...
Found 30 Skills
File-based memory system using Tiago Forte's PARA method. Use this skill whenever you need to store, retrieve, update, or organize knowledge across sessions. Covers three memory layers: (1) Knowledge graph in PARA folders with atomic YAML facts, (2) Daily notes as raw timeline, (3) Tacit knowledge about user patterns. Also handles planning files, memory decay, weekly synthesis, and recall via qmd. Trigger on any memory operation: saving facts, writing daily notes, creating entities, running weekly synthesis, recalling past context, or managing plans.
Obsidian vault management combining qmd (search) and notesmd-cli (CRUD). No Obsidian app needed. Use for: (1) searching notes with keyword, semantic, or hybrid search, (2) creating/editing/moving/deleting notes, (3) daily journaling, (4) frontmatter management, (5) backlink discovery, (6) AI agent memory workflows, (7) vault automation and scripting. Triggers: obsidian vault, obsidian notes, vault search, note management, daily notes, agent memory, knowledge base, markdown vault.
This skill should be used when the user asks to "initialize search", "set up semantic search", "enable qmd", "add search to secondbrain", or mentions wanting to enable semantic search capabilities for an existing secondbrain project.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.
Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.
Use a local QMD knowledge base through UXC over MCP stdio, with daemon-backed session reuse and typed retrieval flows that avoid repeated model warmup and unnecessary query-expansion latency.
This skill should be used to search the local Obsidian vault / markdown knowledge base by meaning, not just keywords, using the on-device qmd engine (BM25 + vector + LLM rerank). Trigger when the user asks to "search my vault/notes", "find notes about X", "what do my notes say about Y", "do I have anything on Z", "semantic search my knowledge base", or wants concept/cross-lingual retrieval over markdown. Fully local — nothing leaves the machine.
Official Salesforce documentation retrieval skill. Prefer locally indexed Salesforce docs via qmd when available; otherwise use Salesforce-aware scraping and guide/PDF discovery strategies for developer.salesforce.com and help.salesforce.com.
Initialize or migrate a repo into the ai-memory pattern: the .ai-memory.toml routing marker (workspace/project), the recall/write routing snippet in CLAUDE.md/AGENTS.md, and the ai-memory MCP server entry. Includes the qmd→ai-memory migration for repos still on the old wiki/qmd stack. Use when the user asks to set up ai-memory in a project (greenfield or brownfield), wire the MCP, enable auto-capture, or migrate off qmd.
Initialize, diagnose, or migrate a project into the LLM wiki pattern with AGENTS/CLAUDE instructions, QMD MCP wiring, Claude/Codex/OpenCode hooks/plugins, guardrails, and QMD doctor checks. Use when the user asks to set up wiki infrastructure, check if a project needs migration, install wiki hooks, or validate QMD.
Comprehensive skill for the `kb` CLI and the Karpathy Knowledge Base pattern. Covers the full KB lifecycle — topic scaffolding, multi-source ingestion (URLs, files, YouTube, bookmarks, codebases), wiki article compilation, cross-article querying with file-back, lint-and-heal passes, QMD indexing, and hybrid search. Also covers codebase-specific analysis via inspect commands for complexity, coupling, blast radius, dead code, circular dependencies, symbol/file lookups, backlinks, and code smells. Use when working with kb CLI commands, knowledge base workflows, code vault generation, code graph analysis, code metrics inspection, wiki compilation, or the ingest-compile-query-lint cycle. Do not use for general code review, linting, formatting, building Go projects, or writing application code.
This skill should be used to watch a long-running background job (ffmpeg/media encode, qmd or other embedding/vector-DB run, batch agent/LLM pipeline, or a real-browser/agent-browser daemon) until it finishes or wedges, then deliver a verdict (done, needs-attention, or blocked) plus the exact next command, without burning dozens of manual poll commands. Triggers on "babysit this job", "watch this until it's done", "ping me when the encode/embed/batch finishes", "is this background process stuck", "monitor this ffmpeg/qmd run", or any request to wait on a long-running process and be told when it's complete or hung.