# Ops Rca Hypothesis Generator

> Generates vendor-neutral root-cause-analysis (RCA) hypotheses from incident symptoms and recent changes, producing a prioritized investigation plan.

- Skill: `sisodiabhumca/ops-rca-hypothesis-generator` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add sisodiabhumca/ops-rca-hypothesis-generator`
- Raw SKILL.md: https://api.skillmd.com/api/skills/sisodiabhumca/ops-rca-hypothesis-generator/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: sisodiabhumca (https://skillmd.com/u/sisodiabhumca)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/sisodiabhumca/ops-rca-hypothesis-generator

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## When to invoke
- After an outage/incident when you have symptoms and a change log but no confirmed cause.
- You want a structured, testable list of hypotheses with next steps.

## Inputs needed
- `--incident`: JSON describing impact window, symptoms, and affected components.
- `--changes`: JSON list of recent changes (deploys, config, infra).
- Optional: `--out`: Path to write hypotheses JSON.

## Workflow
1. Load incident and change entries.
2. Extract keywords from symptoms/components.
3. Score each change by time proximity and keyword overlap.
4. Generate hypotheses:
   - “Change X caused symptom Y via mechanism Z”.
5. For each hypothesis, produce:
   - quick checks (logs/metrics/flags)
   - deeper validation
   - rollback/mitigation options
6. Output top hypotheses sorted by score.

## Output format
JSON with:
- `incident_summary`
- `hypotheses`: list with `rank`, `score`, `hypothesis`, `evidence`, `next_steps`

## Guardrails
- Do not claim certainty; hypotheses must be framed as testable.
- Avoid blaming individuals; focus on systems.
- Keep guidance vendor-neutral (no tool-specific commands).

## Reference code
Use `ops_rca_hypothesis_generator.py`.