> instrumenting a production service, tuning alert rules, designing Grafana dashboards, defining SLOs and error budgets, or reducing alert fatigue.
npx skills add https://github.com/borghei/Claude-Skills --skill observability-designer
Design production-ready observability strategies that combine the three pillars (metrics, logs, traces) with SLI/SLO frameworks, golden-signals monitoring, multi-window burn-rate alerting, and alert-noise optimization.
Before designing the observability strategy, confirm these inputs. If any is unknown or vague, ASK — do not assume:
slo_designer flags)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|------|---------|---------|
| slo_designer.py | Generate SLI/SLO framework, error budgets, and burn-rate alerts from a service definition | python scripts/slo_designer.py --service-type api --criticality high --user-facing true |
| alert_optimizer.py | Analyze alert configs for noise, coverage gaps, and duplicates; emit an optimization report | python scripts/alert_optimizer.py --input alerts.json --analyze-only |
| dashboard_generator.py | Produce Grafana-compatible dashboard JSON with golden signals and role-based views | python scripts/dashboard_generator.py --service-type api --name "Payment Service" |
Load the reference that matches the task — keep this file lean and pull detail on demand:
Covers:
Does NOT cover:
ci-cd-pipeline-builder for deployment pipelines.runbook-generator for runbook authoring.skill-security-auditor for security-focused analysis.| Skill | Integration | Data Flow |
|-------|-------------|-----------|
| runbook-generator | Every burn-rate alert references a runbook; the runbook generator consumes alert definitions to scaffold investigation steps | Alert YAML --> runbook-generator --> Markdown runbook linked in alert annotations |
| ci-cd-pipeline-builder | Deployment events feed into dashboard annotations and alert suppression windows | Pipeline events --> Grafana annotations + Alertmanager silences |
| performance-profiler | Latency SLI breaches trigger profiling; profiler results inform SLO target adjustments | SLO burn-rate alert --> profiler invocation --> refined latency thresholds |
| database-designer | Database SLIs (query latency, connection success rate, replication lag) align with schema-level health checks | DB schema metadata --> SLI metric expressions for database-type services |
| tech-debt-tracker | Error budget depletion signals feed into tech debt prioritization as reliability investments | Error budget reports --> tech debt backlog items with SLO-linked severity |
| release-manager | Release readiness gates check remaining error budget before approving deployments | Error budget API --> release gate pass/fail decision |
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
Design and automate Extract, Transform, Load data pipelines for data integration and analytics
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
Auto-instrument Node.js applications with distributed tracing, metrics, and logs.
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
Take borghei/observability-designer from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.