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Deployment, cloud, containers, CI/CD, monitoring, and infrastructure
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- Managing Portfolio Construction SecondariesStructures secondary portfolio construction with vintage diversification, strategy mix, and geographic allocation optimization. Use when building secondary portfolios, managing allocation targets, or optimizing portfolio composition.Votes: 0GitHub stars: 41
- Building Statistical Arbitrage ModelsConstructs stat arb strategies with pair selection, signal generation, and portfolio optimization under market neutrality constraints. Use when building stat arb models, designing market-neutral strategies, or optimizing pair portfolios.Votes: 0GitHub stars: 41
- Analyzing Unfunded Commitment ExposureEvaluates unfunded commitment obligations with call probability, pacing models, and portfolio-level exposure management. Use when analyzing unfunded exposure, managing commitment pacing, or stress testing capital calls.Votes: 0GitHub stars: 41
- Analyzing Private Credit Market DynamicsMonitors private credit market evolution with AUM growth, competitive dynamics, and spread convergence with broadly syndicated markets. Use when analyzing private credit trends, tracking market evolution, or assessing competitive positioning.Votes: 0GitHub stars: 41
- Analyzing Oilfield Services EconomicsEvaluates OFS sector investments with rig count sensitivity, day rate analysis, and technology adoption curves. Use when analyzing oilfield services, evaluating service company economics, or assessing technology uptake.Votes: 0GitHub stars: 41
- Analyzing Mortgage Backed SecuritiesEvaluates MBS structures with prepayment modeling (CPR/CDR), collateral analysis, and tranche-level credit risk assessment. Use when analyzing MBS, modeling prepayment scenarios, or evaluating residential mortgage pools.Votes: 0GitHub stars: 41
- Analyzing Middle Market Lending DynamicsEvaluates middle-market lending environment with competition analysis, spread trends, and deal structure evolution. Use when analyzing middle-market lending, tracking competitive dynamics, or assessing market conditions.Votes: 0GitHub stars: 41
- Analyzing Market Regime IndicatorsMonitors market regime signals with volatility clustering, correlation dynamics, and liquidity condition assessment. Use when analyzing market regimes, detecting regime shifts, or adjusting strategy for market conditions.Votes: 0GitHub stars: 41
- Analyzing Leveraged Loan MarketsMonitors leveraged loan market conditions with new issue activity, technical dynamics, and CLO demand analysis. Use when analyzing loan markets, tracking CLO activity, or assessing market technical conditions.Votes: 0GitHub stars: 41
- Analyzing Digital Infrastructure AssetsEvaluates data centers, fiber networks, and tower assets with capacity analysis, tenant credit, and technology obsolescence risk. Use when analyzing digital infrastructure, evaluating tower portfolios, or assessing data center investments.Votes: 0GitHub stars: 41
- Analyzing Alpha Signal DecayEvaluates signal half-life, turnover implications, and capacity constraints for systematic alpha factors. Use when analyzing signal persistence, evaluating factor decay, or estimating strategy capacity.Votes: 0GitHub stars: 41
- WranglerCloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.Votes: 0GitHub stars: 117
- Observability Stack| Atributo | Valor | |----------|-------| | **ID** | `sre-observability-stack` | | **Nivel** | 🔴 Avanzado | | **Versión** | 1.0.0 | | **Keywords** | `observability`, `monitoring`, `metrics`, `tracing`, `prometheus`, `grafana`, `jaeger`, `opentelemetry`, `rust` | | **Referencia** | [Google SRE Book](https://sre.google/sre-book/table-of-contents/), [OpenTelemetry](https://opentelemetry.io/) |Votes: 0GitHub stars: 3
- Disaster Recovery Business Continuity| Atributo | Valor | |----------|-------| | **ID** | `sre-disaster-recovery-business-continuity` | | **Nivel** | 🔴 Avanzado | | **Versión** | 1.0.0 | | **Keywords** | `disaster-recovery`, `business-continuity`, `backup`, `failover`, `rpo`, `rto`, `dr-plan` | | **Referencia** | [AWS Disaster Recovery](https://aws.amazon.com/disaster-recovery/) |Votes: 0GitHub stars: 3
- Chaos Engineering| Atributo | Valor | |----------|-------| | **ID** | `sre-chaos-engineering` | | **Nivel** | 🔴 Avanzado | | **Versión** | 1.0.0 | | **Keywords** | `chaos-engineering`, `chaos-monkey`, `litmus`, `failure-injection`, `resilience-testing`, `chaos-experiments` | | **Referencia** | [Chaos Engineering Principles](https://principlesofchaos.org/) |Votes: 0GitHub stars: 3
- Databricks Expert AgentTransforms the assistant into a Senior Databricks Solutions Architect Agent that designs, implements, and reviews production-grade Databricks solutions following official best practices. Enforces Unity Catalog governance, Delta Medallion architecture, DLT expectations, Predictive Optimization, automatic liquid clustering, UC Metric Views, Genie TVFs, Serverless Workflows, and Asset Bundles. Use when working on Databricks projects requiring production-grade solutions with governance, quality, ...Votes: 0GitHub stars: 6
- Databricks Asset BundlesStandard patterns for Databricks Asset Bundles configuration files for serverless jobs, DLT pipelines, dashboards, alerts, apps, and workflows. Use when creating, configuring, or deploying DABs for infrastructure-as-code deployments. Covers mandatory serverless environment configuration, hierarchical job architecture (atomic/composite/orchestrator), DLT pipeline patterns, dashboard resources with dataset_catalog/dataset_schema, SQL Alerts v2 API schema, Apps lifecycle, Python notebook paramet...Votes: 0GitHub stars: 6
- 08 DebuggingUse when a deployed Databricks Apps agent is failing, returning errors, or behaving unexpectedly. Covers systematic debugging of local dev, bundle configuration, deployment, runtime errors, authentication, resource permissions, and Lakebase memory. Track A Step 8. Consumes a deployed app from Step 7. Produces a resolved, healthy agent deployment.Votes: 0GitHub stars: 6
- 07 Deploy And QueryUse when deploying an agent to Databricks Apps and querying the deployed endpoint. Covers databricks apps create, sync, deploy, OAuth token auth, PAT limitations, curl and Python SDK query methods, and the redeploy workflow. Track A Step 7. Consumes evaluation results from Step 6. Produces a running deployed agent on Databricks Apps.Votes: 0GitHub stars: 6
- 06 EvaluationUse when evaluating an agent's response quality and safety before deployment. Covers running agent-evaluate, evaluation dataset format, built-in judges (relevance, groundedness, safety), interpreting results, and customizing eval datasets. Track A Step 6. Consumes a working agent with tools from Steps 1-5. Produces evaluation results and confidence to deploy.Votes: 0GitHub stars: 6
- 07 Production MonitoringUse when setting up live quality monitoring for a deployed agent. Covers registered scorers with sampling, trace archival to Delta, metric backfill, and periodic human review — even if you just want "monitor my agent's safety score in production." Also use when adding conversation-level judges, tuning sampling rates, or building monitoring dashboards from UC trace data. SDLC Step 7.Votes: 0GitHub stars: 6
- 05 Logged Model And Uc RegistrationUse when you need to log an agent to MLflow, register it in Unity Catalog, or promote a new version as champion. Covers the full model lifecycle — even if you just want "log my agent and make it the production version." Also use when setting up MLFLOW_ACTIVE_MODEL_ID for production trace linking, metric-based promotion gating, or rollback. SDLC Step 5.Votes: 0GitHub stars: 6
- 04b Stakeholder SignoffUse after evaluation (Step 4) passes but BEFORE deployment (Step 6). Covers translating technical eval metrics to business-meaningful terms, running a structured review with business and compliance stakeholders, capturing sign-off, and blocking promotion if review-blocking issues remain. Mirrors the "Align with stakeholders before production" phase of the Databricks agents development workflow. SDLC Step 4b. Do NOT use this skill in place of Step 4 eval — this is the gate layered on top of it.Votes: 0GitHub stars: 6
- 04 Evaluation RunsUse when running mlflow.genai.evaluate() to test agent quality before deployment. Covers the predict_fn contract, answer-sheet mode for re-scoring existing outputs, threshold gates, retry wrappers, human feedback sessions, and conversation evaluation — even if you just want "run my benchmarks and tell me pass or fail." Also use when collecting human labels to calibrate automated scorers. SDLC Step 4.Votes: 0GitHub stars: 6