One call. The right facts.
Without abagraph, agents get everything and understand nothing. With it, one call returns exactly what matters: ranked by confidence, deduped, within your token budget.
build_context callSix deterministic steps. Every time.
No prompt engineering. No tuning. No guesswork. The right facts arrive in the right order because the pipeline is deterministic. Each fact’s own confidence score decides where it lands.
{
"tool": "build_context",
"args": {
"seeds": ["acme-corp", "sarah-chen"],
"token_limit": 1200,
"as_of": "now"
}
}
Confidence is the sort key.
Every fact carries a score from 0.00 to 1.00. Context assembly sorts by it. The agent reads the most trustworthy signal first. Below your threshold, the engine excludes it. It never guesses.
This is not a filter you write yourself. It is baked into every fact at write time. The agent receives a packet where every item passed a bar you set, not one the model guessed.
Context compaction is one call. The whole engine is underneath it.
build_context sits on top of bitemporal storage, hybrid recall, source-cited provenance, and a durable agent kernel. One engine, not a patchwork.