Score8.6
Popularity569.0
Risknone
TierGold
Score breakdown
Usefulness9.0
Novelty9.0
Momentum8.0
Maturity9.2
Open-source/build8.4
Evidence8.0
Workflow potential9.7
Setup ease6.4
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for **AI agent operators who need an auditable misalignment diagnostic** — iFixAi runs 45 inspections across fabrication, manipulation, deception, unpredictability, opacity, sabotage, sandbagging, oversight evasion, and power elevation, with a cross-vendor judge so the agent never grades itself, and a reproducible JSON+Markdown report under `./ifixai-results/`. Useful for **CI / pre-deploy
Who should use it
**AI agent operators who need an auditable misalignment diagnostic** — iFixAi runs 45 inspections across fabrication, manipulation, deception, unpredictability, opacity, sabotage, sandbagging, oversight evasion, and power elevation, with a cross-vendor judge so the agent never grades itself, and a reproducible JSON+Markdown report under `./ifixai-results/`**CI / pre-deploy gates** — the CLI (`ifixai run --provider anthropic`) is scriptable, the SUT-vs-Judge pairing is explicit, every run writes a manifest of inputs so a graded result is auditable and replayable, and a Safety & Boundaries sub-50% score caps the overall rating at ★★★ Adequate**AI safety / red teams** — Category K covers ambiguity, prompt injection (file/search/system/sleeper), authority escalation, contradictory params, parameter validation, and tool prohibition, the 13 extended inspections cover sabotage, sandbagging, oversight evasion, and power elevation**Agent builders in regulated industries** — finance, healthcare, legal, hiring, education all need evidence-backed agent-grade artifacts; iFixAi's auditable manifest + cross-vendor judging produces the kind of artifact a regulator will accept**Claude Code users** — the plugin lets Claude operate the diagnostic for you (discover the agent's setup, build the fixture, run it, explain the scorecard), the same 45 inspections and the same auditable manifest as the CLI**Teams evaluating multiple model providers** — cross-vendor judging produces a comparable letter grade across Anthropic, OpenAI, Gemini, Azure, Bedrock, OpenRouter, and a self-hosted model, with the same fixture and the same judge set**Agent builders who suspect their agent is leaking or hallucinating but cannot reproduce the failure** — Category I (Context & State) covers cross-reference, state consistency, multi-turn correction, 6-turn chains, and constraint accumulation, the cases where most agents quietly degradeEvaluation: `pip install 'ifixai[anthropic,openai]'`, `ifixai run --provider anthropic --api-key $ANTHROPIC_API_KEY` (with `OPENAI_API_KEY` in the environment for cross-vendor judging), or open the repo in Claude Code and say `run iFixAi on my setup`; the README walks through the CLI flags, the eval modes, the fixture schema, and the cross-vendor pairing rules
Who should skip it
Move on from ifixai-ai/iFixAi if the licensing terms, language support, or platform requirements do not fit your project.
About this signal
ifixai-ai/iFixAi is tracked by RepoRadar as a apache-2.0 diagnostic for ai age in the ifixai-ai/iFixAi is the Apache-2.0 diagnostic fr section. It was first seen on 2026-06-25 and last updated on 2026-06-25. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. Across RepoRadar's eight signals, ifixai-ai/iFixAi is strongest on workflow potential (9.7) and maturity (9.2) and weakest on setup ease (6.4) — a profile worth weighing against your own priorities. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned ifixai-ai/iFixAi a composite score of 8.6 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 569.0 and never affects the composite score or tier. The risk label of 'none' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Risk explanation
No inherent user-impacting risk is flagged from the captured evidence.
Evidence links
Closest alternatives / related signals
ifixaiifixai-aiai-agent-diagnosticagent-evaluationoperational-misalignmentmisalignment-detectionfabricationmanipulation
