iFixAi: Independent Auditing for AI Agents

TL;DR: iFixAi is an Apache-2.0 Python tool that audits an AI agent’s behaviour, either run by a person or by the agent auditing itself, and claims an answer in under 120 seconds. It has 27,500 stars, 1,507 forks and 5 open issues.

What it is

An evaluation tool for AI agents, and the description frames the question it exists to answer in plain terms: is the agent doing what it is supposed to do. That is the central unresolved question in agent deployment, because agents are shipped on demonstrations and monitored with logs after the fact.

The two modes are stated in the description as well. The audit can be run by a human or by the agent itself. Both matter, and they are not equivalent.

$ curl -s https://api.github.com/repos/ifixai-ai/iFixAi \
  | jq '{stars: .stargazers_count, language, license: .license.spdx_id, topics, created_at}'
{
  "stars": 27500,
  "language": "Python",
  "license": "Apache-2.0",
  "topics": ["agent-evaluation","ai","ai-alignment","ai-evaluation","ai-governance","ai-safety"],
  "created_at": "2026-04-27T13:02:34Z"
}

The topic list is the positioning, and it is a serious one: agent evaluation, alignment, governance, safety. Those four words together put the project in the audit-and-assurance category rather than the debugging category.

Independence is the claim to interrogate

The word in the project name is “independent”, and it is doing real work there. An audit run by the agent itself is self-reporting, and the description is upfront that this mode exists.

That is not a flaw in the tool. It is a property of the situation, and any tool that lets you choose the auditor is telling you the difference matters. What it does mean is that the independence has to come from somewhere other than the runner: from the audit criteria being external to the agent, from the evidence being observed behaviour rather than the agent’s own account of its reasoning.

Ask which of those you are getting before you treat a passing result as a governance artefact. The 120 second turnaround is the more comfortable number in the description, but it is a speed claim, and speed here comes from scope rather than from rigour.

The issue count is unusually low

Five open issues, 1,507 forks, 27,500 stars. That is one issue per 5,500 stars, and the repository was created only in April 2026. Whatever the mechanism, it means the public tracker is not where this project’s history lives.

Metric	Value
Stars	27,500
Forks	1,507
Open issues	5
Primary language	Python
Created	2026-04-27
Last push	2026-10-14
License	Apache-2.0

Last push was 2026-10-14, the day before this post, so the project is plainly active right now.

How to try it

git clone https://github.com/ifixai-ai/iFixAi.git
cd iFixAi

The clone is the verifiable starting point. The audit surface itself lives behind the project site at ifixai.ai, and the repository description does not spell out a command line, so check there for how a run is configured before assuming the source is the whole interface.

When to use it

It fits best as a gate before an agent goes somewhere it can do damage, or before a behaviour change ships. A pre-release check that runs in a couple of minutes is something you can put in a pipeline. A review that takes a day, you will start skipping.

It is also the right shape for the question teams keep deferring: not “is the model aligned” but “does this specific agent, with these specific tools, do what it is supposed to do today”. The second question is narrower and answerable.

When not to use it

Do not use it as a safety guarantee or a compliance certificate. Nothing that produces a verdict in under two minutes is a certification of behaviour across the distribution of tasks your agent will actually see.

Second, if your only evidence is the agent’s own account of what it did, you have measurement and not auditing, regardless of the tool’s name. Keep the evidence outside the system under test.

Source and Accuracy Notes

• Project page: https://www.ifixai.ai
• Source repository: ifixai-ai/iFixAi (verified via GitHub API html_url)
• License: Apache-2.0 (verified via GitHub API license.spdx_id)
• Stars at time of writing: 27500
• The 120 second figure and the dual-runner model are claims from the repository description, not independently measured