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paqad-ai

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Spec-driven development framework — AI agents that think before they type

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--- name: root-cause-analysis description: 'Writes a canonical RCA artifact for an incident or failure. Use when the workflow is root-cause-analysis and the team needs one durable record of problem, evidence, root cause and solution.' metadata: model_tier: reasoning cacheable: 'false' output_format: markdown paqad-meta: skill.meta.yaml --- ## What It Does Produces a canonical root cause analysis document with a fixed section set so investigations stay comparable across stacks and incidents. ## Use This When When the workflow is explicitly root-cause-analysis and the team needs a durable artifact that captures the problem, evidence, root cause, and solution in one place. ## Inputs - Read the incoming problem statement first. - Read the current stack snapshot, logs, traces, tests, or incident notes when available. - Use stack-specific tools and rules only as investigation inputs, not as a reason to vary the RCA structure. ## Procedure 1. Restate the problem clearly and identify the affected stack context. 2. Capture symptoms, impact, and timeline evidence before writing a conclusion. 3. Separate confirmed root causes from contributing factors and open questions. 4. Record the remediation in the `Solution` section even when it is proposed rather than already deployed. 5. End with verification steps and follow-up actions needed to prevent recurrence. ## Output Contract - Match `assets/output.template.md` exactly: 8 canonical sections in the order from `assets/section-order.txt`. - `## Solution` is always present, even when the remediation is proposed not deployed. - Output must pass `scripts/lint-output.sh` (exit 0): it enforces the section order strictly. ## Escalate / Stop Conditions - Ask when there is not enough evidence to distinguish root cause from speculation. - Warn when the available evidence conflicts across logs, tests, or runtime observations. - Do not present a guess as a confirmed root cause. ## Resources - `references/rca-sections.md` - `scripts/lint-output.sh` - `assets/output.template.md` - `assets/section-order.txt` - `agents/openai.yaml`