Datalayer Agent Skills Model Card
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Datalayer Agent Skills Model Card
| Field | Value |
|---|---|
| Repository | datalayer/agent-skills |
| Category | Composable Agent Skills Pack and Runtime Recipes |
| Stars / forks snapshot | 9 / 1 |
| Language | Python |
| License | BSD-3-Clause |
| Raw capture | raw-github/datalayer_agent-skills.md |
| Updated by | hourly public metadata update, 2026-05-30 13:16 +0800 |
1. Role in Self Evolve
datalayer/agent-skills provides composable skill packs and runtime recipes for coding agents with an emphasis on reproducible installation and workflow reuse. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
collect reusable skills as installable packs -> map skills to real workflows and runtime contexts -> version skill definitions to preserve reproducibility -> compose skills into controllable agent workflows with lower setup cost
3. Evidence Path
web-observed GitHub page showed 9 stars, 1 fork, 17 commits, BSD-3-Clause license, and README focus on agent skill packs for practical coding workflows. 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 Composable Agent Skills Pack and Runtime Recipes: 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.