eval-view: Regression testing for AI agents

by hidai25 · MCP Server · ★ 139

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install eval-view

pip install evalview
git clone https://github.com/hidai25/evalview-support-automation-template

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars139
Forks27
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score69/100
Open Issues2
Last Updated2026-10-16
Created2025-11-17
Platformscli, mcp, python
Est. Tokens~24k

About eval-view

The open-source behavior regression gate for AI agents. Think Playwright, but for tool-calling and multi-turn AI agents. Your agent can still return and be wrong. A model or provider update can change tool choice, skip a clarification, or degrade output quality without changing your code or breaking

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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