incident-to-regression

name	incident-to-regression
description	Convert incident artifacts into deterministic regression fixtures and CI-ready outputs. Use when users ask to reproduce a failure, build repeatable graders, or emit junit evidence.
license	Apache-2.0

Incident To Regression

Use this skill to transform an observed incident into deterministic regression checks.

Gait Context

Gait is an offline-first runtime for AI agents that enforces tool-boundary policy, emits signed and verifiable evidence artifacts, and supports deterministic regressions.

Use this skill when:

• incident triage needs repeatable regression fixtures
• CI gate failures need deterministic reproduction
• evidence outputs must be generated from Gait artifacts

Do not use this skill when:

• Gait CLI is unavailable in the environment
• no Gait run/pack artifact or run identifier is available as input

Required Inputs

• run_source: run id, runpack path, or equivalent source accepted by gait regress init.
• workdir: writable working directory where fixtures and outputs will be created.

Workflow

1. Resolve run_source before changing directories:
   • keep identifiers unchanged (for example run ids)
   • if run_source is a relative file path, normalize to absolute path
   • run_source_ref="$(python3 -c 'import os,sys; v=sys.argv[1]; print(os.path.abspath(v) if os.path.exists(v) else v)' <run_source>)"
2. Enter the declared working directory before generating artifacts:
   • mkdir -p <workdir> && cd <workdir>
3. Initialize deterministic fixture from the incident source:
   • gait regress init --from <run_source_ref> --json
4. Parse fields from init output and record them:
   • ok, run_id, fixture_name, fixture_dir, config_path, next_commands
5. Execute regression graders:
   • gait regress run --json
6. If CI evidence is needed, rerun with JUnit output:
   • gait regress run --json --junit <junit_path>
7. Return a concise summary with:
   • source identifier
   • fixture directory and config path
   • status and failed grader count
   • evidence output paths

Safety And Portability Rules

• Use CLI outputs only; do not infer grader results from config text.
• Treat non-zero regress exit codes as actionable outcomes, not warnings.
• Do not assume repository-specific fixture paths.
• Keep paths relative to the active workspace unless the user explicitly asks for absolute paths.

Usage Example

run_source_ref="$(python3 -c 'import os,sys; v=sys.argv[1]; print(os.path.abspath(v) if os.path.exists(v) else v)' run_demo)"
mkdir -p ./regress-workdir && cd ./regress-workdir
gait demo --json
gait regress init --from "${run_source_ref}" --json
mkdir -p ./artifacts
gait regress run --json --junit ./artifacts/junit.xml

Expected result:

• init output includes ok=true and a fixture_dir
• run output includes stable status and grader failure details
• JUnit file exists at ./artifacts/junit.xml

Validation Example

mkdir -p ./regress-workdir && cd ./regress-workdir
gait demo --json
gait regress init --from run_demo --json
mkdir -p ./artifacts
gait regress run --json > ./artifacts/regress_result.json
python3 - <<'PY'
import json
from pathlib import Path
p = json.loads(Path('./artifacts/regress_result.json').read_text(encoding='utf-8'))
assert p.get('status') in {'pass', 'fail'}
print('validated status:', p.get('status'))
PY

Expected result:

• script prints validated status: pass or validated status: fail

Provider Notes (Anthropic Claude)

• Ask Claude to use the incident-to-regression skill by name when this workflow applies.
• Keep outputs grounded in command results and --json payload fields.