Find published results for DNA, RNA, protein and cell models in the Rewire benchmark graph, and reproduce or run benchmarks locally with rewirebench.
Plugin bio-model-benchmarks from marketplace rewire-benchmarks in rewire-bio/rewire-benchmarks. Commands read from the repo's manifest — 26 days ago.
This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.
bio-model-benchmarksFind published benchmark results for biological models (DNA, RNA, protein, single-cell and molecular models) in the Rewire benchmark knowledge graph, and reproduce or run a benchmark locally with rewirebench against the user's own model or configuration, then compare the run with the published resul
rewire-benchmark-graphruns: uvx --from git+https://github.com/rewire-bio/[email protected] rdf-kg-mcp serve https://benchmarks.rewirebio.io/agents/kg.tar.gz
MetaHarness integration — surfaces score/genome/mint/mcp-scan/threat-model via skills; pairs with @metaharness/router (ADR-148/149) for cost-optimal model routing; honors ADR-150 optional-augmentation constraint
13 skills · 1 command · 1 agent · hooks
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
26 skills · 4 commands · 3 agents · 1 MCP server
Carta Investors plugin — skills for querying investors data, performance benchmarks, regulatory reporting, AGM deck generation, brand extraction, and more via the Carta MCP server
29 skills · hooks
Autonomous experiment loop — optimize any file by a measurable metric. 5 slash commands (/autoresearch-agent:setup, /ar-run, /ar-loop, /ar-status, /ar-resume), 8 built-in evaluators, configurable loop intervals (10min to monthly).
6 skills · 1 agent · hooks
Comprehensive context engineering and harness engineering skills for production-grade AI agent systems: fundamentals, degradation patterns, compression, optimization, self-managed context (model-controlled live context editing), multi-agent coordination, long-horizon prompting (pseudo-formal task briefs for long-running and parallel agents), memory systems, tool design, filesystem context, hosted agents, evaluation, autonomous harnesses, self-improvement loops (RSI, meta-harnesses, evolutionary scaffold search), latent briefing (KV cache sharing between agents), project development, and cognitive architecture. Ships with a researcher operating system (rubrics, mechanism registry, claim provenance, run state machine, adversarial benchmarks, continuous loop).
19 skills
LLM benchmarking and evaluation including lm-evaluation-harness, BigCode Evaluation Harness, and NeMo Evaluator. Use when benchmarking models or measuring performance.
98 skills
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.