docs/DESIGN.md

Design Notes

Purpose

Most memory benchmarks measure semantic recall in benign settings.

This benchmark targets retrieval failure modes that matter in agent memory systems:

• retrieving the wrong person
• retrieving the wrong environment
• retrieving an outdated fact instead of the current one
• retrieving something semantically close but operationally wrong

Benchmark principles

• retrieval-focused, not generation-focused
• one query, many plausible distractors
• exact relevant entry ids are known in advance
• metadata such as tags, depth, speaker, and timestamp may be present but are optional
• cases should remain small enough to inspect by hand

Scoring

Suggested scoring:

• Recall@1
• Recall@5
• MRR
• error bucket counts by adversary_type

Expansion ideas

• more software-specific adversaries
• benchmark splits by domain
• fact-update and contradiction-specific suites
• Hugging Face dataset packaging