Ross ROSS = Recommend OSS · open-source software intelligence for agents

ifixai-ai/iFixAi

Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds. observed · 2026-08-28

github.com/ifixai-ai/iFixAi · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

81/100

  • Activity 99
  • Release rhythm 99
  • Longevity 9

Flags: young

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 6
  • age_days: 128
  • days_rel: 9
  • days_push: 8
  • n_releases_24m: 18

Full methodology

Adoption not part of the score

11173 stars · 1134 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

iFixAi is an open-source CLI diagnostic tool that independently audits AI agents for misalignment, hallucination, manipulation, deception, and opacity. It runs guided or flag-driven inspections across five pillars and produces an A–F graded scorecard in under two minutes.

Use cases

  • audit an AI agent for hallucinated citations and fabricated sources
  • detect prompt injection and manipulation vulnerabilities in an agent
  • check whether an agent is doing the job it is supposed to do
  • generate an audit trail for AI compliance and governance
  • test agent behavior against EU AI Act and NIST AI RMF requirements
  • evaluate agent consistency and unpredictability across runs
  • run red-teaming style diagnostics on an LLM agent before deployment

When to choose

  • you need fast, repeatable auditing of AI agent behavior and alignment
  • you must demonstrate compliance with AI governance frameworks like EU AI Act, ISO 42001, or NIST AI RMF
  • you want to catch fabrication, manipulation, and opacity failures before shipping to users
  • you prefer a CLI workflow with guided setup or explicit flags

When to avoid

  • you need deep continuous observability or tracing of production agent traffic rather than point-in-time audits
  • you only need token efficiency, latency, or infrastructure benchmarking
  • you require a fully managed commercial audit with certification guarantees

Facets

cli-tool · maturity active

testing monitoring security llm-inference agent-framework benchmarking artificial-intelligence security developer-tools testing python cli cross-platform ai-auditing agent-evaluation ai-governance ai-safety hallucination-detection prompt-injection eu-ai-act iso-42001 nist-ai-rmf owasp-llm risk-assessment responsible-ai llm-security misalignment-detection ai-agents

3 sources

Member repositories

RepositoryRoleHealth v2
ifixai-ai/iFixAimain81

For agents

markdown · JSON · MCP: product_card(name="ifixai-ai/iFixAi")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem