github search·dataarctech-bayesian-agent
DataArcTech/Bayesian-Agent
DataArcTech/Bayesian-Agent: LLM agents increasingly rely on external inference conditions: prompts, tools, memory, SOPs, skills, and harness feedback. These assets can improve task execution without changing model weights, but they are often revised by heuristic reflection or by reusing observed successe...
AgentScore
13.2+0.12
+0.12 vs 24h ago
Adoption9.8
Quality0.0
Momentum55.6
Community12.6
Quality unrated · weight redistributed
CapabilitiesCode GenerationMemory
DeploymentIde Plugin
MaturityExperimental
Score breakdown
Headline plus the four pillars over time. Click any pillar below to see the signals feeding it.
Not enough score history in this window yet — try a wider one.
Pillar contributions
- GitHub stars+5.7%56→ 29.3MCP registry listing0→ 0.0
Pillar = mean of 2 scaled values = 9.8.
Awaiting first reading — these signals apply to this agent and will be ingested on the next tier tick: PyPI monthly installs, SO questions (7d), Product Hunt upvotes, Docker Hub pulls, Crates.io downloads (90d), Tech-news mentions (30d)
Not applicable — this agent doesn't have the prerequisite (no GitHub repo, no HF mirror, etc.) for these signals to ever apply: HF downloads (30d), npm weekly installs
Embed badgeShow your AgentTape rank on your project README
Markdown
[](https://agenttape.com/agents/dataarctech-bayesian-agent)
HTML
<a href="https://agenttape.com/agents/dataarctech-bayesian-agent"><img src="https://agenttape.com/api/badge/dataarctech-bayesian-agent.svg" alt="AgentTape" /></a>
Similar
Vibe-search via embedding cosine
Score envelope last computed 5h ago.