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This is the most important page on this site. Everything else describes what InterpScout does; this page describes the rule that everything else is built to obey: a prompt is never a guarantee. Every piece of data a user can see has a write path, and every write path that matters has a mechanical check sitting in front of it — code that verifies, not a model that promises.

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The rule, concretely

An LLM deciding a course’s glossary is good is not the same thing as a course’s glossary being good. So InterpScout doesn’t let an agent’s self-report be the last word on anything that ends up in front of a teacher or a student:
  • A course can’t save with a term the save tool can’t locate verbatim in the source text — see Document Workshop for the full gate stack.
  • A briefing can’t save under roughly 800 characters, or without at least three real, verified further-reading links — see Briefing Pipeline.
  • A briefing save is rejected outright if the row it’s writing to isn’t still running — a stale session doesn’t get to overwrite a newer result.
  • The production line runs a single LLM call per task — one agent session with full context — rather than a chain of smaller, stateless calls, which is what lets sourcing and reasoning stay coherent across the whole document.
When a gate rejects, that isn’t treated as a failure — it’s an instruction. The agent reads the specific reason and tries again inside the same session. Only a source that’s genuinely unusable ends production with a clear explanation instead of a result. The system also runs a handful of small background sweeps that repair gaps mechanically rather than requiring a person to notice them — re-segmenting sentences a course was missing, re-classifying an article whose subject field never got set, and similar cleanup. None of it is dramatic; all of it is the same instinct applied at smaller scale: don’t leave a silent gap, close it with a deterministic pass.

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Verified against production reality

Every gate here is grounded in production reality, not theory: each targets a write path validated against real agents on real sources. The discipline is consistent — define exactly what a gate must guarantee, encode it as a deterministic check, and pin it with a test so the guarantee holds permanently. The same discipline governs how fixes ship. A change to the content line does not count as finished until it survives a real end-to-end run against the real model and real search, watched from dispatch to a saved, gate-passing artifact — first locally, then in production.

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Why this page exists

A system that asks to be trusted should be able to say precisely what stands between a model’s output and a student’s screen. On this platform the answer is never “a well-written prompt.” It is a stack of small, deterministic checks, each independently verifiable — and that is the point.