Skip to main content
BitsWeave
Onboarding

Explore context

Use the /app/context explorer to traverse your org's context graph from a focal set and stream a prose summary — then call the same context API manually for structured output.

Once an agent is connected, its work builds up a context graph in your org: activity rows, ranked idents, and the relations between entities. The context explorer at /app/context lets you pick a focal set and see the graph plus a live prose summary. The same data is available over the context API for agents and scripts.

What you're looking at

Context is assembled from your org's procedure log + identity graph. You start from a focal set — one or more idents (a project, an agent, a member, …) — and BitsWeave traverses outward to find what co-occurred and what's related. See the MCP surface for how agents reach the same data.

Using the explorer (/app/context)

Open the explorer in the app:

Open the context explorer

It's a form over a view panel. The whole view is URL-driven — the focal set, depth, and budget live in the query string, so any walk you build is shareable and bookmarkable. Pasting a link reproduces the same walk.

Build a focal set

Each row in the Focal set form is one ident: a Kind dropdown plus a value control.

  • For graph-backed kinds — Project, Agent, Member, User, Note, Decision — the value control is an autocomplete: start typing and pick a match.
  • For free-text kinds — Organization, Agent run — type the id directly.

Add more rows with Add ident to seed a multi-ident walk; remove rows you don't want. At least one completed ident is required before you can explore.

Organization isn't a focal kind

The form lists Organization, but af-api rejects org as a focal ident — your active org is already implicit from your membership. If you pick it, the explorer surfaces a clean error rather than running the walk. Use a concrete entity (project, agent, …) as your focal seed instead.

Tune depth and budget

Two knobs shape the walk:

  • Depth (0–3, default 1) — how many hops out from the focal set to traverse.
  • Budget (1–1000, default 200) — the cap on nodes the walk visits.

Explore

Press Explore. The form submits as a GET — the params write to the URL, the loader runs context.graph with them as focal idents (org resolved server-side from your session pin), and the view panel renders the resulting graph (nodes + edges) below. If the walk fails (e.g. a forbidden focal kind, or idents that span multiple orgs), you get a clean error banner instead of the graph.

Read the summary

Alongside the graph, the sidebar calls context.query with the focal idents and no query text. It paints claims first, then appends a streamed prose answer.

Using the context API manually

The explorer is a thin client over af-api's context.* procedures. Agents call them as MCP tools; you can also hit the RPC endpoint directly. All of them are gated on the context:read scope, and the org is never a parameter — it's inferred from your org-bound idents (or your active-org binding for context.graph).

ProcedureShapeUse it for
context.searchqueryWhich nodes match free text. Returns ranked idents to pass on as focal idents.
context.graphqueryHow nodes relate. No focal idents: the org-wide pin map. With focal idents: that focal neighborhood.
context.hydratequeryWhat a node is: per-entity snapshots for a focal set. No walk, no graph.
context.querystreamingWhat the nodes mean. mode: "evidence" returns ranked evidence and excerpts; answer adds claims and prose.

The focal input for context.graph and context.query:

  • focalIdents — array of { kind, id } (1–50). org is rejected as a kind.
  • depth — 0–3 (default 1).
  • budget — 1–1000 (default 200).

A direct call for a focal neighborhood:

curl -G 'https://bitsweave.com/api/rpc/context.graph' \
  -H "Authorization: Bearer $AGENTFLOW_TOKEN" \
  --data-urlencode 'input={"json":{"focalIdents":[{"kind":"project","id":"<project-id>"}],"depth":1,"budget":200}}'

The response carries nodes (each with a label), edges (with relation, source, and strength), and meta.

From an agent, query is the read

context.graph returns the structure around the focals. context.query returns the evidence, and in answer mode claims and prose, for the same focals. The sidebar calls context.query with no query text.

Walks can be bounded out

A dense graph at high depth can hit the walk timeout — af-api returns a BAD_REQUEST telling you to lower depth or narrow the focal set rather than hanging or 500-ing. Start at depth 1 and widen only if you need to.

Where this fits

The explorer and the API are the read side of everything your connected agent produces. With an org joined, an agent connected, and context flowing, you've completed onboarding — explore the Concepts and Guides next.

Connect your agents

Connect the AI agents you already run to BitsWeave in three steps — add the MCP server over OAuth, install af-tap with the af-tap-install skill, then verify by creating an artifact and watching a live session.

What is BitsWeave

Connect the coding agent you already use to a shared platform that tracks your work, gives it a memory, and lets it act across your tools.

On this page

Using the explorer (/app/context)Build a focal setTune depth and budgetExploreRead the summaryUsing the context API manuallyWhere this fits