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Module 5 Agent Skill

Teaching instructions for Module 5 (Authentication and Authorization) — use when module_id is module-5

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/langchain-ai/lca-deployment --skill module-5

What comes with it

8 579 bytes besides the instruction
information.md

The instruction itself

7 sections, as written by the author

Module 5 — Authentication and Authorization

Lesson Title

Authentication and Authorization in a Multi-Tenant Deployment

Goal

Walk the student through adding real auth to a LangGraph deployment: first identifying users (@auth.authenticate), then scoping their access to resources (@auth.on), then swapping the toy token store for a real identity provider, then wiring it into the tutor agent.

How to run this lesson

  • Start with the distinction: authentication answers "who is this?", authorization answers "what can they do?". The two decorators map cleanly to those two questions.
  • Walk through m5.1's request-pipeline diagram before touching code. Students should know where in the request lifecycle the auth handler runs.
  • For m5.2 (local auth), emphasize that @auth.authenticate is the ONLY interception point and that its return value flows into the rest of the request.
  • For m5.3 (private conversations), the key idea is metadata stamping on writes + filter dict on reads. Bob gets a 404 (not 403) on Alice's thread because the filter makes the thread invisible — there's nothing to forbid.
  • For m5.4 (Supabase), call out that the @auth.on handler from m5.3 does NOT change — only @auth.authenticate is swapped. This is the payoff for keeping auth and authz decoupled.
  • For m5.5 (tutor), reinforce that deep_tutor's store_namespace is email-derived (independent of auth identity). Auth gates "can this user call?" while namespace decides "where does their data live?". They meet in @auth.on.store().

Key concepts to cover

  • @auth.authenticate — receives the raw Authorization header, returns a MinimalUserDict with at minimum identity, or raises Auth.exceptions.HTTPException(401)
  • @auth.on — fires after authenticate, on every resource access; stamps metadata on writes and returns a filter dict on reads
  • The langgraph.json registration — auth.path = "./auth.py:auth" is what wires the handler in
  • Scoped vs broad handlers — @auth.on.threads.create is more specific than @auth.on; most specific wins
  • Why Bob gets a 404 (filter, not deny) — the resource is invisible, not forbidden
  • @auth.on.store() is different — no automatic filter, the handler asserts/raises to allow/block; namespace[0] convention
  • Swapping the token store — from hardcoded dict (m5.2) to Supabase JWT validation (m5.4); only @auth.authenticate changes
  • Two access paths to the authenticated user — ctx.user.identity in @auth.on handlers, runtime.server_info.user.identity in graph nodes
  • The OAuth2 three-role model — Client App, Auth Provider, Agent Server; the Agent Server never stores credentials

10. Auth vs namespace in deep_tutor — auth gates calls; context.store_namespace (email-derived) decides where data lives; meeting point is @auth.on.store()

Tone guidance

Precise about the contract — students often confuse authentication with authorization. Hammer the separation. When discussing examples, refer to Alice/Bob/admin (the lesson personas) so the student can connect explanations to concrete lab runs.

Reference material

Full reference material is in information.md in this directory. Read it before answering factual questions.

How to use it

Copy the folder

Take langchain-ai/module-5 from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.