incident-to-regression

Convert incident artifacts into deterministic regression fixtures and CI-ready outputs.

12|5|Updated Feb 5, 2026
One-click install
npx skills add https://github.com/Clyra-AI/gait --skill incident-to-regression-clyra-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: incident-to-regression
Source: https://github.com/Clyra-AI/gait/tree/main/.agents/submissions/anthropic/incident-to-regression
Command: npx skills add https://github.com/Clyra-AI/gait --skill incident-to-regression-clyra-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Incident artifacts often exist as ad-hoc evidence that is hard to reproduce in CI. This skill converts those artifacts into deterministic regression fixtures and CI-ready outputs that can be replayed and validated.

Core Features & Use Cases

  • Initialize deterministic fixtures from an incident source using gait regress init.
  • Parse initialization outputs to extract fixture metadata and next steps.
  • Execute regression graders to validate consistency and produce CI-friendly reports (e.g., JUnit).
  • Use cases include incident triage, reproducible failure reproduction, and automated evidence generation for PRs and audits.

Quick Start

Provide a run_source (run id, runpack path, or equivalent) and a writable workdir, then run gait regress init to create deterministic fixtures, followed by gait regress run to generate regression outputs for CI.

Frequently Asked Questions about incident-to-regression

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

FAQPage Schema
How do I turn incident evidence into regression fixtures for CI?

Incident evidence can be turned into regression fixtures by initializing deterministic artifacts from an incident source and executing regression runs to produce CI-ready outputs. This process converts ad-hoc evidence into repeatable, validated tests.

What's the best way to generate JUnit reports from incident artifacts?

To generate JUnit reports from incident artifacts, execute regression graders after initializing deterministic fixtures from your incident source. This validates consistency and produces CI-friendly reports suitable for automated testing pipelines.

How do I reproduce a CI failure using deterministic fixtures?

You can reproduce a CI failure by providing the run source and a writable working directory to initialize deterministic fixtures. Running the regression process replays the observed incident for consistent failure reproduction.

Do I need a specific run source to create regression artifacts?

Yes, creating regression artifacts requires a run source, such as a run id or runpack path, along with a writable working directory. These inputs allow the initialization process to extract fixture metadata and next steps.

Can I use incident triage artifacts for automated PR evidence generation?

Incident triage artifacts can be used for automated PR evidence generation by converting them into deterministic regression fixtures. Running regression validations produces CI-ready outputs that serve as reproducible evidence for pull requests and audits.

Why are my ad-hoc incident artifacts hard to reproduce in CI pipelines?

Ad-hoc incident artifacts are hard to reproduce in CI because they lack deterministic structure. Converting them into regression fixtures standardizes the evidence, enabling consistent replay and validation within automated CI environments.