forecast-accuracy-analyzer
Forecast accuracy measurement and improvement skill with error decomposition
warehouse-simulation-modeler
Discrete event simulation skill for warehouse design validation and capacity planning
transportation-spend-analyzer
Freight spend analysis and benchmarking skill for cost optimization and carrier negotiation support
supply-chain-visibility-platform
End-to-end supply chain visibility skill providing real-time tracking and control tower capabilities
logistics-kpi-tracker
Comprehensive logistics performance measurement skill with KPI tracking, benchmarking, and improvement recommendations
incoterms-compliance-checker
International shipping terms validation and documentation skill ensuring trade compliance
demand-sensing-integrator
Real-time demand sensing skill integrating POS data, market signals, and external factors for responsive planning
carbon-footprint-calculator
Logistics carbon emission tracking and reduction planning skill supporting sustainability initiatives
spend-analytics-engine
Procurement spend analysis skill with classification, consolidation, and savings identification
scor-kpi-dashboard-builder
SCOR-aligned supply chain KPI dashboard design and implementation skill
cost-to-serve-analyzer
Supply chain cost-to-serve analysis skill by customer, product, or channel
ds-plan
REQUIRED Phase 2 of /ds workflow. Profiles data and creates analysis task breakdown.
ds
Orchestrates 5-phase data analysis workflow with output-first verification.
csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
rag-auditor
Produzir auditoria de colapso semantico em RAG, taxonomia hierarquica e schema de Graph-RAG para sistemas de recuperacao. Usar quando o usuario pede diagnostico de alucinacao/queda de precisao em vector stores, arquitetura RAG hierarquica ou grafo de conhecimento.
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
conversation-analyzer
Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.
Azure AI Services
This skill should be used when the user asks about "Azure AI Search", "Cognitive Search", "AI Foundry", "Azure OpenAI", "speech to text", "text to speech", "Azure AI", "vector search", "semantic search", or mentions Azure AI and cognitive services. Provides best practices and MCP tool guidance for Azure AI services.
xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
process-mining-assistant
Perform an end-to-end process mining analysis via a command-line workflow that progressively ingests, profiles, cleans, mines and reports on event logs using PM4Py. The workflow generates stage-based artefacts (including versioned notebooks) and pauses at decision checkpoints so the user can validate findings and choose how to proceed.
data-analyzer
データ分析と可視化を行うスキル
morning-metrics
Pull daily metrics briefing from Gmail, Calendar, and Substack. Use when "check my metrics", "morning metrics", "show my stats", "what's my day look like".
speckit-analyze-zh
对spec.md、plan.md和tasks.md三个核心文档进行非破坏性跨工件一致性和质量分析。在任务生成后识别不一致、重复、模糊和规范不足的项目。触发词包括："speckit-analyze"、"speckit分析"、"文档一致性分析"、"规范分析"、"质量检查"、"工件分析"、"spec分析"、"plan分析"、"task分析"。
model-convergence-forecast
Forecast convergence patterns in multi-model consensus scenarios.
adaptive-temporal-analysis-integration
Integrate adaptive temporal analysis for drift detection.
neutral-target-baseline
Establish neutral baseline metrics for unbiased assessment.
longitudinal-drift-detector
Detect behavioral drift and alignment degradation over time.
polymorphic-analytics-instantiation
Instantiate polymorphic analytics for multi-context analysis.
symbol-map-entropy-calc
Calculate entropy metrics for symbolic mapping and semantic drift.
predictive-persona-performance
Predict persona performance in specific task contexts.
data-gouv
Skill professionnel pour Claude Code permettant d'accéder, télécharger et analyser les données ouvertes françaises via data.gouv.fr. Inclut une librairie Python complète, des exemples de code, et une documentation détaillée des datasets les plus utilisés.
xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
aggregating-gauge-metrics
Aggregate pre-computed metrics (gauge, counter, delta types) using OPAL. Use when analyzing request counts, error rates, resource utilization, or any numeric metrics over time. Covers align + m() + aggregate pattern, summary vs time-series output, and common aggregation functions. For percentile metrics (tdigest), see analyzing-tdigest-metrics skill.
detecting-anomalies
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier detection (Z-score, IQR), threshold-based alerts, rate-of-change detection with window functions, and moving average baselines. Choose pattern based on data distribution and anomaly type.
field-extraction-parsing
Extract structured fields from unstructured log data using OPAL parsing functions. Covers extract_regex() for pattern matching with type casting, split() for delimited data, parse_json() for JSON logs, and JSONPath for navigating parsed structures. Use when you need to convert raw log text into queryable fields for analysis, filtering, or aggregation.
analyzing-apm-data
Monitor application performance using the RED methodology (Rate, Errors, Duration) with Observe. Use when analyzing service health, investigating errors, tracking latency, or building APM dashboards. Covers when to use metrics vs spans, combining RED signals, and troubleshooting workflows. Cross-references working-with-intervals, aggregating-gauge-metrics, and analyzing-tdigest-metrics skills.
working-with-intervals
Work with Interval datasets (time-bounded data) using OPAL. Use when analyzing data with start and end timestamps like distributed traces, batch jobs, or CI/CD pipeline runs. Covers duration calculations, temporal filtering, and aggregating by time properties. Intervals are immutable completed activities with two timestamps, distinct from Events (single timestamp) and Resources (mutable state).
aggregating-event-datasets
Aggregate and summarize event datasets (logs) using OPAL statsby. Use when you need to count, sum, or calculate statistics across log events. Covers make_col for derived columns, statsby for aggregation, group_by for grouping, aggregation functions (count, sum, avg, percentile), and topk for top N results. Returns single summary row per group across entire time range. For time-series trends, see time-series-analysis skill.
filtering-event-datasets
Filter and search event datasets (logs) using OPAL. Use when you need to find specific log events by text search, regex patterns, or field values. Covers contains(), tilda operator ~, field comparisons, boolean logic, and limit for sampling results. Does NOT cover aggregation (see aggregating-event-datasets skill).
analyzing-tdigest-metrics
Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine pattern with align + m_tdigest() + tdigest_combine + aggregate. For simple metrics (counts, averages), see aggregating-gauge-metrics skill.
analyzing-text-patterns
Extract and analyze recurring patterns from log messages, span names, and event names using punctuation-based template discovery. Use when you need to understand log diversity, identify common message structures, detect unusual formats, or prepare for log parser development. Works by removing variable content and preserving structural markers.
time-series-analysis
Analyze event datasets (logs) and intervals over time using OPAL timechart. Use when you need to visualize trends, track metrics over time, or create time-series charts. Covers timechart for temporal binning, bin duration options (1h, 5m, 1d), options(bins:N) for controlling bin count, and understanding temporal output columns (_c_valid_from, _c_valid_to, _c_bucket). Returns multiple rows per group for time-series visualization. For single summaries, see aggregating-event-datasets skill.
xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
python-polars
This skill should be used when the user asks to "work with polars", "create a dataframe", "use lazy evaluation", "migrate from pandas", "optimize data pipelines", "read parquet files", "group by operations", or needs guidance on Polars DataFrame operations, expression API, performance optimization, or data transformation workflows.
transcript-analyzer
This skill analyzes meeting transcripts to extract decisions, action items, opinions, questions, and terminology using Cerebras AI (llama-3.3-70b). Use this skill when the user asks to analyze a transcript, extract action items from meetings, find decisions in conversations, build glossaries from discussions, or summarize key points from recorded meetings.
health-data
Query Apple Health SQLite database for vitals, activity, sleep, and workouts. Supports Markdown, JSON, and FHIR R4 output formats. This skill should be used when analyzing health metrics, generating health reports, answering questions about fitness or sleep patterns, or exporting health data in standard formats.
causal-inference-root-cause
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
forecast-premortem
Use to stress-test predictions by assuming they failed and working backward to identify why. Invoke when confidence is high (>80% or <20%), need to identify tail risks and unknown unknowns, or want to widen overconfident intervals. Use when user mentions premortem, backcasting, what could go wrong, stress test, or black swans.
bayesian-reasoning-calibration
Use when making predictions or judgments under uncertainty and need to explicitly update beliefs with new evidence. Invoke when forecasting outcomes, evaluating probabilities, testing hypotheses, calibrating confidence, assessing risks with uncertain data, or avoiding overconfidence bias. Use when user mentions priors, likelihoods, Bayes theorem, probability updates, forecasting, calibration, or belief revision.
plausible
Plausible Analytics API for querying website statistics and managing sites. Use this skill to get visitor counts, pageviews, traffic sources, and manage analytics sites.
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