Agent skill · alirezarezvani
agent-regression-evals
Use before shipping any agent, prompt, model or tool change, or when a pass-rate drop needs a verdict. Runs repeated trials, gates candidate vs baseline with paired statistics in regression_gate.py, checks tool-call trajectories and finds flaky cases.
What it needs
About 3k tokens when loaded.
What this skill does
Agent Regression Evals — prove the change did not make it worse Portability: 3 stdlib scripts, no APIs, no LLM calls. You run the agent; these grade, count and gate. "Pass rate went from 82% to 79%" is not a finding until you know whether three points is outside the noise. Agents are non-deterministic, so one trial per case cannot tell a regression from a coin flip, and a final answer can be right while the path to it called a tool it never should have. Workflow Step 1 uses match modes strict unordered subset superset. Default to superset (required steps present, harmless exploration allowed); grade the outcome, not the path, unless order is the requirement. forbidden tools block in every mode. Step 2 reports pass@k (succeeds at least once in k) and pass^k (succeeds all k times). A user meets every trial, so pass^k is the reliability number. Cases marked critical are never quarantine candidates. Step 3 averages trials within each case first (trials of one case are correlated), then tests paired per-case differences with a t-based 95% CI and a one-sided exact McNemar test. When the drop is real but the sample is too small to show it, the gate says how many cases it would take. The gate blocks on 1. A statistically significant drop (CI upper bound below zero, or McNemar p < 0.05). 2. A critical case that passed every baseline trial and failed any candidate trial. 3. A baseline case missing from the candidate run. Dropping a case is the cheapest fake fix. 4. A quarantine entry with no owner or expiry, or covering a critical case. 5. A forbidden tool call (trajectory checker, exit 4). It warns, and a human decides, on an underpowered drop above --tolerance or a cost rise above --max-cost-increase. Hard rules Never compare single trials. Under 3 trials per case the flake detector refuses (exit 4). Never pool trials as independent samples. Average per case, then compare cases. Never quarantine without owner and expiry. An expired entry re-enters the gate automatically. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills alirezarezvani/agent-regression-evals