Build blueprint
Context Window Admission Controller
A component scoring every candidate memory, file, or message before context assembly.
- Problem
- Agents overfill context with available material instead of admitting only task-relevant evidence.
- Why Jev
- Hundreds of inclusion decisions may be needed for a single model request.
- Architecture
- Task + candidate metadata/snippets → relevance Scores → diversity and token-budget algorithm → context.
- Current alternative
- Top-k embeddings and recency heuristics.
- Jev advantage
- Allows semantic admission at a granularity that full LLM ranking makes expensive.
- Unknowns
- Whether independent scoring preserves cross-item diversity.
Why this confidence: Clear economic leverage from many decisions per expensive request.
This is an authored hypothesis derived from the research corpus. Nothing here demonstrates product demand, or that Jev performs well on this particular workload. Run the validation experiment before building past the MVP.
Sources
Limitations
- Whether independent scoring preserves cross-item diversity.
- This is a research hypothesis, not evidence of product demand or Jev performance in this workflow.
Supporting research
- Decision quorum PlausibleMultiple typed judgments are aggregated through voting or confidence-aware stopping.
- typesafe-mcp ObservedAn MCP server exposing TypeSafe evaluation to coding agents.
- Cheap decision calls could make tens or hundreds of semantic judgments per event economical. SpeculativeThe product design follows from published pricing and parallel question primitives, not independent production evidence.
- Parallel decision matrix PlausibleOne state is evaluated against many named questions, replacing repeated prompt/parse cycles.