# AI use cases for iFixAi (ifixai-ai/iFixAi) Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Use cases: 5 | Page: https://dedupedai.com/use-cases/ifixai-ai-ifixai/ iFixAi is an open-source Python tool that audits whether an AI agent is doing the job it is supposed to do, using 60 inspections that combine red-teaming with operational checks. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Audit your agent in a guided terminal wizard: https://dedupedai.com/use-cases/ifixai-ai-ifixai/guided-audit-of-my-agent/ - Have Claude Code run and explain the audit: https://dedupedai.com/use-cases/ifixai-ai-ifixai/let-claude-code-run-the-audit/ - Run a scripted audit in CI with explicit flags: https://dedupedai.com/use-cases/ifixai-ai-ifixai/scripted-audit-in-ci/ - Get a citable grade from a second-vendor judge: https://dedupedai.com/use-cases/ifixai-ai-ifixai/citable-cross-vendor-grade/ - Add an /ifixai-skill audit command to Cursor: https://dedupedai.com/use-cases/ifixai-ai-ifixai/scaffold-audit-skill-for-cursor/ ## How to audit your agent in a guided terminal wizard with iFixAi Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Run a 10-inspection audit of your agent with a setup wizard and get a scorecard in minutes. **Who it is for:** A developer who has built an AI agent and wants a quick, repeatable check before shipping changes. **The problem:** Eval and red-teaming tools mostly measure technical traits like latency and prompt injection, not whether the agent does its actual job. **The outcome:** A saved configuration and a graded report in ./ifixai-results/ covering the default 10 inspections. ### Steps 1. Run `pip install "ifixai[openai]"` (swap in the extra for the provider you will test). 2. Run `ifixai setup` and pick your provider, model, judge, and suite with the arrow-key wizard. 3. Run `ifixai run` to start the audit; no flags are needed after setup. 4. Open the JSON and Markdown reports in ./ifixai-results/ and review the failing inspections. ### Prompt to paste into your agent ```text Use the iFixAi repo at ifixai-ai/iFixAi to audit my agent at . Run the guided wizard with `ifixai setup` followed by `ifixai run`, then report the overall grade and the list of failing inspections. Verify that the reports were written to ./ifixai-results/ before you summarize. ``` ### Caveat A grade is citable only when a different vendor's judge grades the agent; a single-vendor run is a smoke test. Risk, credentials: The wizard stores only the name of the environment variable in ifixai.yaml, but your API key itself must still be kept out of shared files and logs. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/ifixai-ai-ifixai/guided-audit-of-my-agent/ ## How to have Claude Code run and explain the audit with iFixAi Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Install the iFixAi plugin so Claude Code can discover your setup, run the audit, and walk you through results. **Who it is for:** A developer working in Claude Code who wants an agent to run the audit and explain the scorecard without writing commands. **The problem:** Setting up an audit, choosing judges, and reading the scorecard takes time when done by hand for every change. **The outcome:** An interactive scorecard, produced by the agent, that explains which behaviors passed or failed. ### Steps 1. Inside Claude Code, run `/plugin marketplace add ifixai-ai/iFixAi`. 2. Run `/plugin install ifixai@ifixai-community`. 3. Restart Claude Code or run `/reload-plugins` if the plugin does not appear. 4. Ask Claude Code: "run iFixAi on my setup", or type `/ifixai:ifixai`. ### Prompt to paste into your agent ```text Install the iFixAi plugin from ifixai-ai/iFixAi in this Claude Code session, then run an audit on the model with judge . Report the cost estimate the agent shows before the run, then the scorecard. Verify that the agent named the cost before billing started. ``` ### Caveat The plugin path is documented for Claude Code and Codex; the same engine runs underneath as the CLI. Risk, credentials: The agent reads provider keys from environment variables, so make sure those keys are set only in environments you trust. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/ifixai-ai-ifixai/let-claude-code-run-the-audit/ ## How to run a scripted audit in CI with explicit flags with iFixAi Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Difficulty: Advanced | Time: 30 minutes | Basis: From the README Add a fully scriptable iFixAi run to a pipeline using explicit flags and no interactive wizard. **Who it is for:** A platform or DevOps engineer who wants a repeatable agent check on every build without human prompts. **The problem:** Interactive setup does not fit automated pipelines, so the audit must be driven by flags and environment variables. **The outcome:** A pipeline step that writes JSON and Markdown reports on each run, with a no-key smoke test available. ### Steps 1. Run `pip install "ifixai[anthropic]"` in the pipeline environment. 2. Run `ifixai run --provider mock --api-key not-used --eval-mode self` to confirm the pipeline works without keys or network. 3. Export your provider key as an environment variable in the CI secret store. 4. Run `ifixai run --provider anthropic --api-key "$ANTHROPIC_API_KEY" --eval-mode self` and archive the reports in ./ifixai-results/. (inferred, check the README) ### Prompt to paste into your agent ```text Use the iFixAi repo at ifixai-ai/iFixAi to add a CI step that audits . Use explicit flags with no wizard, run the mock smoke test first, then the real run. Verify that the smoke test output shows a failing scorecard for B01 and P01, which is expected from the bundled default fixture. ``` ### Caveat The smoke test shows that the pipeline runs, not that the agent is good, and --eval-mode self results are not citable. Risk, credentials: The key is passed through the --api-key flag, so keep it in the CI secret store and avoid echoing it in build logs. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/ifixai-ai-ifixai/scripted-audit-in-ci/ ## How to get a citable grade from a second-vendor judge with iFixAi Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Difficulty: Advanced | Time: 45 minutes | Basis: From the README Grade your agent with a judge from a different vendor so the result can be cited. **Who it is for:** A team lead who needs an audit result to show a customer, auditor, or internal review board. **The problem:** A grade where the agent grades itself is not credible evidence of how it behaves. **The outcome:** A report in ./ifixai-results/ where a different vendor's judge graded your agent, making the grade citable. ### Steps 1. Run `pip install "ifixai[anthropic,openai]"` to install the SDKs for both the agent and the judge. 2. Export `ANTHROPIC_API_KEY` for the agent under test and `OPENAI_API_KEY` for the judge. 3. Run `ifixai run --provider anthropic --api-key "$ANTHROPIC_API_KEY" --fixture ./my-fixture.yaml`. 4. Check the report to confirm the judge came from a different provider than the agent under test. ### Prompt to paste into your agent ```text Use the iFixAi repo at ifixai-ai/iFixAi to produce a citable grade for using a judge from a different vendor and my fixture at . Verify in the report that the judge provider differs from the agent provider and that the run is not flagged as self-judged before you report the grade. ``` ### Caveat Without your own fixture, the bundled default seeds defects on purpose, so its failures will appear on your scorecard unless you pass --fixture. Risk, credentials: Two provider keys are needed, and both will be used for paid API calls, so restrict them to the audit account. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/ifixai-ai-ifixai/citable-cross-vendor-grade/ ## How to add an /ifixai-skill audit command to Cursor with iFixAi Repo: [ifixai-ai/iFixAi](https://github.com/ifixai-ai/iFixAi) | Difficulty: Intermediate | Time: 15 minutes | Basis: From the README Scaffold a native audit command into Cursor with one zero-install command, then run it from the chat. **Who it is for:** A developer who uses Cursor and wants to run an agent audit from inside the editor without a plugin install. **The problem:** Not every agent has a plugin, and manual setup of an audit workflow is easy to get wrong. **The outcome:** A /ifixai-skill command in Cursor that reads your setup, shows the cost through a dry run, and runs only after you confirm. ### Steps 1. Run `uvx ifixai install --agents cursor` in your project folder. 2. Open Cursor and run `/ifixai-skill` in the chat. 3. Let the skill read your setup and show the cost from its dry run. 4. Reply yes only after you have reviewed the cost, so the run starts. ### Prompt to paste into your agent ```text Use the iFixAi repo at ifixai-ai/iFixAi to scaffold the audit skill into this Cursor project with `uvx ifixai install --agents cursor`, then run `/ifixai-skill` to audit . Report the dry-run cost estimate before any paid call. Verify that no run started until I approved the estimate. ``` ### Caveat The skill needs uv and Python 3.10 or newer on the machine, and auto-detection only finds agent folders that already exist. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/ifixai-ai-ifixai/scaffold-audit-skill-for-cursor/