a2a-inspector: Validation Tools for A2A Agents

by a2aproject · Agent Tool · ★ 509

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

How to install a2a-inspector

git clone https://github.com/a2aproject/a2a-inspector.git
docker run -d -p 8080:8080 a2a-inspector

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 67/100

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. Full audit →

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.

Quick Facts

Stars509
Forks158
LanguageTypeScript
CategoryAgent Tool
LicenseApache-2.0
Quality Score67/100
Open Issues26
Last Updated2026-11-06
Created2025-06-10
Platformsnode
Est. Tokens~15k

About a2a-inspector

A2A Protocol Inspector The A2A Inspector is a web-based tool designed to help developers inspect, debug, and validate servers that implement the A2A (Agent2Agent) protocol. It provides a user-friendly interface to interact with an A2A agent, view communication, and ensure specification compliance. The application is built with a FastAPI backend and a TypeScript frontend.

Compatible Skills

These tools work well together with a2a-inspector for enhanced workflows:

  • lucid-agents — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • awesome-a2a — semantic(0.44)+complementary+similar_pop (45%)

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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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