fix-agent-issue
Fix or change an AI agent's behavior using MLflow traces and regression tests. Use for wrong or incomplete answers, hallucinations, missing tool calls, new business rules, trace-driven debugging, or context and token-cost optimization. Diagnose the actual failure, plan a test, implement the smallest fix, and verify the new behavior without breaking existing cases.
Install
With your agent
Install OMGSkills skill "mlflow/skills:fix-agent-issue" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/mlflow/skills /tmp/skills && ln -s /tmp/skills/fix-agent-issue ~/.claude/skills/fix-agent-issueFrom README
Fix Agent Issue The user wants to change an AI agent's behavior — either because something is wrong (pointing at a trace, pasting an answer they didn't like, describing a failure mode) or because they're introducing a new requirement, business rule, or policy ("lead with our premium line," "never reveal internal docs," "always confirm the order ID first"). A new business rule is not a bug, but it earns the same discipline: it's a behavior change that can silently break other behaviors, so it goes through the loop too. They want the change made with confidence that it sticks and doesn't regress anything else. Drive a disciplined improvement loop, never a one-shot patch. The non-negotiable loop EXPLORE → PLAN → IMPLEMENT → VERIFY, in that order. Don't skip phases. Don't edit anything in EXPLORE. Don't write code in PLAN. Don't change tests in VERIFY.
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