How-to guides

Task-oriented recipes. A how-to guide answers "how do I X?" for a reader who already knows what they're trying to do.

• Add Hadron to Claude Code (OAuth) — the shortest path: register the Hadron MCP server and sign in with OAuth in three steps. No API keys, no skills. Start here when onboarding a new engineer.
• Use Hadron slash commands in Claude Code — install the hadron plugin for explicit /hadron:h-task, /hadron:h-search, and /hadron:h-open-node commands. Needs the OAuth connector above as a prerequisite.
• Install Hadron with the install script — one-liner setup for .mcp.json + the Hadron Spec Kit extension in a coding-agent project.
• Install Hadron in Claude Desktop — OAuth-based install: paste the MCP URL, sign in once in the browser, no copy-paste of secrets. Production + local-dev (cloudflared) paths.
• Install Hadron in VS Code — same OAuth flow for VS Code's built-in MCP support.
• Install the hadron CLI — Homebrew/archive/Go install, browser or token sign-in, and pointing AI agents at the CLI.
• Manage your API keys — mint user-scoped API keys for scripts and CLI tools, see every key issued on your account (portal + OAuth), and revoke leaked keys instantly.
• Building an agent — set up memories, expose an agent through an app, configure it for AI tools.
• Installing an agent — what "install" means at each level — the org-level vs. user-level install disambiguation.
• Building a chatbot agent — wire up a Hadron agent that drives a conversational AI chatbot.
• Configure your LLM provider — pick a provider (Anthropic, OpenAI, GLM, AWS Bedrock), enter a key, test it.
• Configure AWS SageMaker for vector embeddings — point your Hadron server at an existing SageMaker endpoint for the RAG vector index: env vars, a dedicated IAM principal, and verification.
• Run local LLMs with llama.cpp — the free, offline dev backend for the RAG vector index on macOS / Apple Silicon: a local nomic-embed-text endpoint, plus chat models with one-line start/stop scripts.
• Adding nodes to a memory — add nodes from the portal UI, including the auto-slug behavior, advanced types, and conflict / validation errors.
• Export a task node as a Claude Code skill — publish any task node as a SKILL.md that Claude Code auto-triggers; the node stays the source of truth (edit and re-export). Covers the required claudeSkill properties and the by-hand procedure.
• Maintain product specs — capture durable product rules as citation-addressed spec nodes with hadron spec: scaffold, lint, find, and supersede.
• Build a conditional conversation flow — author edge conditions so a stage is skipped when its data is already on file.
• Run a guided coding session — use the 6-phase guided-session pattern in Claude Code with a worked end-to-end example.
• Sync a memory from a Git repo — back a memory with a GitHub repo: layout, auth, sync mechanics, and conflict handling.
• Use Obsidian to view/edit memory — open a synced or exported memory repo as an Obsidian vault, with the Front Matter Title plugin to make citation-numbered nodes readable.
• Deleting a memory — remove a memory through the portal's Danger-zone affordance, who's authorized for which memory class, and how soft-delete and recovery work.
• Allow your agent to ask for uploads — enable the asset-upload tool on an agent and verify the end-to-end flow.
• Test personas — automated chatbot testing: define a persona once, run it repeatedly, get a pass/fail report.
• Portal chat testing — manual smoke-test checklist for the per-agent Chat tab.
• Debug PERMISSION_DENIED errors — decision tree for memory-access errors: find the closed gate, run a diagnostic query, fix it.