mykg

Set up and maintain the GitHub Pages site for the mykg repo (SenolIsci/mykg) — a purpose-built pages/ folder (landing page adapted from README.md, blog posts, diagrams), built by a GitHub Actions workflow that runs Jekyll and deploys the result to a gh-pages branch. Use whenever the user wants to publish project documentation or blog articles as a website, create a landing page, turn the project into a public site, enable/configure/troubleshoot GitHub Pages or the gh-pages branch, add a new page/blog post/diagram to the published site, fix a broken/failing Pages build, or asks things like "can we get a docs site for mykg", "I want a landing page based on README", "publish this blog article", "is Pages enabled yet", "the pages workflow failed", or "add this new doc to the site". Also trigger on custom domain / CNAME requests for the project site. Scoped to the mykg repo's own pages/ folder and its gh-pages publishing pipeline — not for unrelated new project sites.

Run mykg knowledge-graph commands inside Claude Code from one slash command `/mykg`. The user describes intent in natural language (extract, append, resume, approve, walkthrough, parse-docs, fetch-web, query); the skill parses intent, builds the right `mykg` CLI command from the live `--help` output, confirms, runs it, and drives the inbox/outbox watch loop for LLM-bearing commands (extract-graph). For read-only queries, prefers MCP tools when the mykg MCP server is online, falling back to reading session files directly. Ensures `.mcp.json` is configured (with user approval). Excludes `mykg init` (interactive shell command) and `mykg merge-graphs` (follow-up planning).

Reviews the current codebase architecture and proposes improvements using four parallel specialist subagents: System Architect, Software Architect, Data Architect, and an Adversarial Architect that red-teams failure paths, LLM adversarial output scenarios, silent corruption risks, and invariant bypasses. Each subagent independently analyzes the codebase from their domain perspective, then their findings are consolidated into a living `architecture.md` file with a tracked to-do list and change log. Use this skill whenever the user asks to review, analyze, audit, or improve the architecture — or when they ask questions like "what should we change structurally?", "how is the system organized?", "what are our architecture problems?", "can you do an architecture review?", or "let's redesign X". Also trigger when the user mentions technical debt, structural improvements, security concerns, failure modes, vulnerabilities, or wants a second opinion on design decisions, even if they don't use the word "architecture".

Build, analyze, and visualize networks and graphs using NetworkX (Python). Use this skill whenever the user wants to: create graphs or networks, analyze graph properties, compute centrality measures, find shortest paths, detect communities, run graph algorithms, convert graphs to/from matrices or dataframes, visualize networks with matplotlib, import/export graph files (GML, GraphML, GEXF, edgelist, etc.), work with directed or undirected graphs, weighted or multigraphs, perform social network analysis, or do any graph theory computation. Trigger on keywords: networkx, graph, network, nodes, edges, adjacency, shortest path, centrality, community detection, spanning tree, flow, clique, PageRank, bipartite, DAG, topology, graph analysis, social network.