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git clone https://github.com/r5rana/agentware.git
cd agentware
git checkout 3c25cdd
claude "hi"
git clone https://github.com/r5rana/agentware.git
cd agentware
git checkout 3c25cdd
codex "hi"

This installs agentware, the open-source engine behind memfor. No tagged release yet. These commands pin commit 3c25cdd.

Apache-2.0. No memfor account. Needs macOS or Linux (Windows via WSL), git, Python 3, bash, jq, and Claude Code or Codex.

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Run e8cb9c5 LongMemEval-S, recorded 25 June 2026, 08:19:48 UTC.

  • dirty tree · not cited
  • determinism ok
Reproduce this number
Benchmark metrics
Metric Value Definition
Recall@5 0.9140 Mean over questions of |evidence ∩ top-k| / |evidence|.
nDCG@5 0.8831 With binary relevance.
MRR 0.9104 Mean of 1/rank of the first evidence session.
Precision@5 0.3328 Mean over questions of |evidence ∩ top-k| / k. It can't reach 1 when a question has fewer than k evidence sessions, so it is shown on receipts only.
Conditions
Queries 470
k 5
Strategy bm25
Gold path benchmarks/longmemeval/longmemeval_s_cleaned.json
Tests ran 271
Tests failed 0
Environment Hardware, OS and Python version: not recorded for this run.
Ledger row 71
Raw row 
{"ablation": null, "checks": {"determinism_ok": true, "index_validate_ok": true, "test_pass_rate": 1.0, "tests_failed": 0, "tests_ran": 271}, "commit": "e8cb9c5", "committed": "2026-06-25T06:37:05Z", "dirty": true, "gold_path": "benchmarks/longmemeval/longmemeval_s_cleaned.json", "metrics": {"latency_ms_mean": 10.59455399103017, "latency_ms_p50": 10.606416006339714, "mrr": 0.9103777978731046, "ndcg_at_k": 0.8830615827171846, "precision_at_k": 0.33276595744680854, "recall_at_k": 0.9140425531914894}, "mode": "eval", "num_queries": 470, "reliability": 96.56, "run": "2026-06-25T08:19:48Z", "schema": "agentware-bench/v1", "strategy": "bm25", "subject": "chore(autocommit-message-fix): agentware-autocommit-message-derivation, agentware-init", "suite": "longmemeval", "top_k": 5}
reliability is an internal composite health score (0–100), not a benchmark metric.
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