How to give agents fresh context without giving them fresh hallucinations
A technical pattern for supplying agents with current web facts, source evidence, uncertainty and a safe route to human review.
Written by
Scraper.io
Editorial
An agent with stale context can make a confident decision about a market that no longer exists. An agent with unverified scraped text can be even worse: the context is fresh, but its meaning is unsupported.
The safer pattern is to deliver structured facts together with evidence, observation time and an explicit uncertainty state.
Make provenance part of the schema
Do not attach citations as a decorative array after generation. Every supplied value should point to the observation that supports it and say whether the value was stated directly, inferred or disputed.
This lets the agent carry evidence into its output and apply different policies to different classes of fact.
Use freshness policies by field
A company name may stay useful for months. A public price or active job opening may need to be checked daily. One dataset-level timestamp cannot express that difference.
Set a freshness policy for each decision-relevant field and prevent expired values from silently presenting as current.
Route uncertainty instead of hiding it
When evidence conflicts or an important value is missing, the system should produce a reviewable state rather than manufacture a clean answer.
Agents can continue with low-risk work, ask for clarification or route the record to a person depending on the policy attached to that field.
A useful agent context layer does not eliminate uncertainty. It makes uncertainty visible and actionable.
Freshness, provenance and review state turn web data into context an agent can use responsibly. Without those controls, retrieval only makes unsupported confidence arrive faster.