zicato-triage-stuck-loop

Diagnose zicato evolution loops with read-only health checks and SQLite index inspection.

4|2|Updated May 14, 2026
One-click install
npx skills add https://github.com/pedapudi/zicato --skill zicato-triage-stuck-loop
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: zicato-triage-stuck-loop
Source: https://github.com/pedapudi/zicato/tree/main/skills/zicato-triage-stuck-loop
Command: npx skills add https://github.com/pedapudi/zicato --skill zicato-triage-stuck-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill diagnoses zicato evolve loops that run without improving, distinguishing weak evaluation signals, overly difficult boards, restrictive mutation rules, and proposer repetition so operators can apply the right contract or steering change.

Core Features & Use Cases

  • Evaluation Health Diagnosis: Use zicato health findings to identify degenerate scoring, flat drift, dead judges, non-differentiating entries, and stalled rejection patterns.
  • Decision-Tree Troubleshooting: Determine whether to revise the board or scoring contract, relax an over-demanding goal, adjust the Forbidden set, or re-steer the proposer through the brief.
  • Read-Only Investigation: Inspect tournament, loss-profile, experiment, and patch history with safe commands and SQL queries before spending LLM budget or starting a new evolution round.
  • Use Case: When several generations are rejected, use this Skill to determine whether the board cannot distinguish candidates, the task is too hard, the needed mutation is forbidden, or the proposer is repeating an ineffective idea.

Quick Start

Use the zicato triage skill to diagnose the current stuck evolve loop using read-only health checks and index queries, then recommend the appropriate contract or steering edit.

Frequently Asked Questions about zicato-triage-stuck-loop

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why does my evolution loop keep rejecting candidates without improving scalar scores?

Rejected candidates and flat scalar improvements indicate a stuck evolution loop caused by degenerate evaluation signals, overly difficult boards, restrictive Forbidden sets, or repetitive proposer behavior. Diagnosing these specific conditions determines the correct contract or steering change to restore progress.

How do I diagnose weak evaluation signals in a stalled evolution run?

Diagnosing weak evaluation signals involves running read-only zicato health checks and SQLite index inspections to identify flat drift, dead judges, or non-differentiating entries before adjusting the board or scoring contract.

What is the best way to troubleshoot a zicato evolution loop that is stuck on repeated rejections?

The best way to troubleshoot repeated rejections is to inspect tournament, loss-profile, experiment, and patch history with safe read-only SQL queries, then determine whether to revise the board, relax an over-demanding goal, or adjust the Forbidden set.

Can I inspect SQLite index diagnostics without spending LLM budget on a new evolution round?

You can inspect SQLite index diagnostics and run read-only zicato health checks without spending LLM budget, allowing you to review board, scoring, and proposer-brief contracts safely before starting a new evolution round.

When should I adjust the Forbidden set or re-steer the proposer brief during prompt mutation?

You should adjust the Forbidden set or re-steer the proposer brief when health checks reveal the needed mutation is forbidden or the proposer is repeating an ineffective idea, preventing the evolution loop from distinguishing candidates.

Does zicato triage work for flat drift and dead judges in evaluation health checks?

Zicato triage works for flat drift and dead judges by applying read-only health findings to decision-tree troubleshooting, distinguishing whether the board cannot distinguish candidates or the task is simply too hard.