Agents ✦ 74outlineNot a production recipe — calibrate thresholds

Tool-result context sieve

Who: Long sessions. Steps: Each tool result → Noul admit-to-context → keep/drop. Expected effect: Less junk in window (sibling to compaction).

Source: https://github.com/GhalebDweikat/winnow ↗ Docs / source ↗

Treat this as an outline — adapt state and questions to your data.

Implement in code — call System One / Jev; compose answers yourself.

Gate on confidence — act, confirm, or escalate before side effects.

Outline sketch

Prompt

# Tool-result context sieve
State: relevant software state for this pattern.
Ask: Choice / Score / Noul questions that close the decision space.
Then: compose the route or action in code; escalate when confidence is low.

Needs access to: typesafe-sdk

Who it's for

Long sessions

Steps / how it's set up

Steps

Each tool result.
Noul admit-to-context.
keep/drop.

Sources

Metrics and demo claims are author-reported or cookbook-reported unless you measure them yourself. Calibrate on your data.

Expected effect

Less junk in window (sibling to compaction)

Unofficial outline for learning. Paraphrased from public docs and tutorials — not a production recipe. Review sources before you automate anything.