AgentFlow
Cost & Performance

Context optimization

Collect, score, compress, and pack repository context before agents run.

Context optimization

Context optimization is implemented in application/internal/contextopt: a collector gathers candidate files, a relevance scorer ranks them, a reducer or compressor trims low-value material, and a packer emits the blob agents actually see. The intent is to send smaller, better-targeted context to paid APIs while keeping the reduction rules inspectable from the CLI.

Pipeline

flowchart LR
  C[Collect files] --> R[Relevance score]
  R --> X[Compress / reduce]
  X --> P[Context pack]
  P --> A[Agent prompt]

CLI

agentflow context billing-v2 --task task-003
agentflow context billing-v2 --task task-003 --optimize
agentflow work "develop billing-v2" --show-context-plan

work runs context optimization in the V3 pipeline unless --no-context-reduction is set.

Configuration

Investigation limits that cap grep output and large files are shared with local investigation: they live under mcp.investigation in config and apply even when the MCP server is disabled, because they govern the local tooling that feeds the collector.

Trade-offs

BenefitLimit
Smaller promptsMay drop relevant files if heuristics miss
Faster cloud callsNot a substitute for reading critical paths manually