Problem
Agent context today is static markdown files baked into the agent definition. This works for simple instructions but breaks down when:
- Context needs to stay current (API docs, runbooks, internal wikis)
- Multiple agents share the same reference material (duplication + drift)
- Context is large and only conditionally relevant
Proposal
Add a context block to agent definitions that supports pointers — URLs, file paths, or doc references that are fetched/resolved at runtime rather than inlined statically.
context:
- url: https://docs.stripe.com/api/charges
cache: 1h
- url: https://internal.notion.so/runbook-deploys
- file: ./shared/style-guide.md
The runtime would fetch and inject these into the agent's prompt at session start (and optionally refresh mid-session for long-running agents).
Why this matters
Static context doesn't compound. If a doc updates, every agent referencing it is stale until someone manually copies the new version. Context pointers make agents automatically current — closer to how humans actually use reference material.
Open questions
- Caching strategy — TTL per pointer? Content-hash based?
- Auth for private URLs (internal wikis, Notion, Confluence)
- Size limits / truncation for large docs
- Should pointers support conditional inclusion (only fetch if agent hits a certain topic)?
Problem
Agent context today is static markdown files baked into the agent definition. This works for simple instructions but breaks down when:
Proposal
Add a
contextblock to agent definitions that supports pointers — URLs, file paths, or doc references that are fetched/resolved at runtime rather than inlined statically.The runtime would fetch and inject these into the agent's prompt at session start (and optionally refresh mid-session for long-running agents).
Why this matters
Static context doesn't compound. If a doc updates, every agent referencing it is stale until someone manually copies the new version. Context pointers make agents automatically current — closer to how humans actually use reference material.
Open questions