github verified Safe content atomic container

ai-fit-tracker

ai-fit-tracker — zitaharry-ai-fit-tracker. Use this tool when you need to track and analyze AI model performance and fitness across different versions and iterations. It solves problems related to model optimization, comparison, and selection by providing a standardized interface for logging and retrieving model metrics. The ai-fit-tracker takes in model performance data as input and outputs comparable metrics and visualizations, ideal for use in machine learning development and deployment contexts.

Cognium trust score
95%
Tier
Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.

Scan details: Circle-IR · 2026-09-28 · Appeal

View full trust & usage report →

Metadata

Version
1.0.0
Skill type
atomic
Execution layer
container
Source
GitHub
Author type
human
Last scanned
2026-09-28
Updated
2026-09-28
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Use via MCP

MCP

Resolve ai-fit-tracker from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
Swap --scope user for --scope project to commit it to .mcp.json.

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