Interactive wizard to design an SLO with SLI, target, error budget, and burn-rate alerts
Scanned 9/8/2026
Install to Claude Code
npx -y skills add agisota/old-one --skill claude-skills__.gemini__skills__slo-design --agent claude-codeInstalls into .claude/skills of the current project.
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---
description: Interactive wizard to design an SLO with SLI, target, error budget, and burn-rate alerts
---
# /slo-design
Step through SLO design using the `slo-architect` skill. Produces an SLO definition, computes error budget + multi-window burn-rate alerts, and runs the reviewer to catch common bugs.
## Usage
```
/slo-design
/slo-design --service checkout-svc --sli-type request-success-rate --target 99.9
```
## Implementation
```bash
SKILL=engineering/slo-architect/skills/slo-architect
# Step 1: gather inputs (service, sli-type, target, window, owner)
# Step 2: render SLO definition
python "$SKILL/scripts/slo_designer.py" \
--service "$SERVICE" \
--sli-type "$SLI_TYPE" \
--target "$TARGET" \
--window-days "$WINDOW_DAYS" \
--owner "$OWNER" \
--policy-doc "$POLICY_DOC" \
--format json > .slo.json
# Step 3: compute error budget + burn-rate alerts
python "$SKILL/scripts/error_budget_calculator.py" \
--target "$TARGET" \
--window-days "$WINDOW_DAYS"
# Step 4: render the markdown SLO for peer review
python "$SKILL/scripts/slo_designer.py" \
--service "$SERVICE" \
--sli-type "$SLI_TYPE" \
--target "$TARGET" \
--window-days "$WINDOW_DAYS" \
--owner "$OWNER" \
--policy-doc "$POLICY_DOC"
# Step 5: validate against the reviewer
echo "=== After saving the SLO, run slo_review.py against the doc ==="
```
## Output
A markdown SLO definition with:
- Service, owner, user journey
- SLI type with numerator/denominator expressions
- Target, window, error budget
- Multi-window burn-rate alert thresholds (PromQL-shaped)
- Review cadence
## Pre-conditions
- `slo-architect` skill installed
- Service identified
- 30 days of historical SLI data available (to pick a sustainable target)
- Error budget policy doc exists or will be created
## Post-conditions
- `.slo.json` written for use with downstream tools (chaos-engineering blast radius, etc.)
- Markdown SLO streamed for review
- Recommendation printed: PASS / WARN / FAIL on `slo_review.py` checks
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