Tiermem Model Card
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Tiermem Model Card
| Field | Value |
|---|---|
| Repository | FreedomIntelligence/Tiermem |
| Category | Provenance-Aware Memory Benchmark Framework |
| Stars / forks snapshot | 5 / 1 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/freedomintelligence_tiermem.md |
| Updated by | hourly public metadata update, 2026-05-29 10:08 +0800 |
1. Role in Self Evolve
Tiermem introduces benchmark tasks that jointly evaluate memory answer quality and provenance consistency for long-term AI assistants. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
construct knowledge-memory tasks with provenance labels -> run language-agent memory retrieval and generation pipelines -> score both answer quality and citation provenance -> compare memory frameworks under standardized settings
3. Evidence Path
web-observed GitHub page showed 5 stars, 1 fork, 24 commits, MIT license, and README framing around provenance-aware memory evaluation. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Provenance-Aware Memory Benchmark Framework: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.