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Found 271 Skills
Pipeline analysis composite. Pulls deal/meeting data from any CRM or tracking system, analyzes the pipeline over a user-defined period (weekly, fortnightly, monthly, quarterly), and produces both an executive summary and a detailed diagnostic report. Covers volume, qualification rates, source effectiveness, stage velocity, stuck deals, and actionable recommendations. Tool-agnostic — works with any CRM (Salesforce, HubSpot, Pipedrive, Close, Supabase, CSV).
Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers on tasks involving: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, WAIC, model comparison, or causal inference with do/observe.
Production server monitoring stack covering Prometheus, Node Exporter, Grafana, Alertmanager, Loki, and Promtail on bare-metal or VM Linux hosts. USE WHEN: - Setting up monitoring for a new production server or VPS - Configuring Prometheus scrape targets for application or system metrics - Creating Grafana dashboards and datasource provisioning - Writing Alertmanager routing rules with email/Slack notifications - Implementing the PLG stack (Promtail + Loki + Grafana) for log aggregation - Performing live system diagnostics with htop, iotop, nethogs, ss, vmstat, iostat - Setting up uptime monitoring with UptimeRobot or healthchecks.io DO NOT USE FOR: - Kubernetes-native observability (use the kubernetes skill instead) - Application-level APM (distributed tracing with Jaeger/Tempo — use observability skill) - Cloud-managed monitoring (CloudWatch, GCP Monitoring, Azure Monitor) - Windows Server monitoring
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by main printing-press SKILL.md (Phase 4.85) and printing-press-polish SKILL.md during the diagnostic loop. Not for direct user invocation — its actionable wrappers are /printing-press and /printing-press-polish.
Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"
Build deterministic forecast scripts with Earth2Studio (model, data source, IO, inference). Do NOT use for ensemble, diagnostics, data-only fetch, or install.
Use when encountering BUILD FAILED, test crashes, simulator hangs, stale builds, zombie xcodebuild processes, "Unable to boot simulator", "No such module" after SPM changes, or mysterious test failures despite no code changes - systematic environment-first diagnostics for iOS/macOS projects
Advanced sub-skill for scikit-learn focused on model interpretability, feature importance, and diagnostic tools. Covers global and local explanations using built-in inspection tools and SHAP/LIME integrations.
Guide for creating high-quality, user-friendly diagnostics in Biome. Use when implementing error messages, warnings, and code frame displays. Examples:<example>User needs to create a diagnostic for a lint rule</example><example>User wants to add helpful advice to error messages</example><example>User is improving diagnostic quality</example>
Evidence-based test debugging enforcing systematic root cause analysis. Use when tests are failing, pytest errors occur, test suite not passing, debugging test failures, or fixing broken tests. Prevents assumption-based fixes by enforcing proper diagnostic sequence. Works with Python (.py), JavaScript/TypeScript (.js/.ts), Go, Rust test files. Supports pytest, jest, vitest, mocha, go test, cargo test, and other frameworks.
Comprehensive debugging toolkit for Gamma integration issues. Use when you need detailed diagnostics, request tracing, or systematic debugging of Gamma API problems. Trigger with phrases like "gamma debug bundle", "gamma diagnostics", "gamma trace", "gamma inspect", "gamma detailed logs".
Unified setup entrypoint for install, diagnostics, and MCP configuration