Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Comprehensive documentation guide for Golang projects, covering godoc comments, README, CONTRIBUTING, CHANGELOG, Go Playground, Example tests, API docs, and llms.txt. Use when writing or reviewing doc comments, documentation, adding code examples, setting up doc sites, or discussing documentation best practices. Triggers for both libraries and applications/CLIs.
A curated, installable collection of Claude Code agent skills covering development, writing, productivity, and knowledge management workflows.
Dimensionality reduction in very large datasets using Siamese Networks
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.
A collection of opinionated agent skills for Claude Code, including sparring, design, planning, and auditing workflows.
17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimizing observability costs.
>-
Analyzes cloud infrastructure and architectures to identify wasted spend and right-sizing opportunities.
Build PFC 5.0 asphalt-mixture specimens with explicit aggregate objects, a declared homogenized-mastic or fine-particle abstraction, residual air voids, measured gradation conversion, contact-pair assignment, compaction, equilibrium, and mass-volume closure; use before Marshall, rutting, creep, or strength tests.
Investigate and reduce SigNoz telemetry ingestion cost and metric cardinality across metrics, logs, and traces. Find what drives SigNoz spend (via the Cost Meter), which metrics have runaway or unbounded label cardinality, and safe, dashboard-, alert-, and Infra-page-aware ways to cut volume. Make sure to use this skill whenever the user asks "why is my SigNoz bill so high", "what's driving my ingestion cost", "reduce telemetry volume", "which metrics cost the most", "cardinality health check", or "what can I safely drop" — or otherwise asks about telemetry spend, ingestion volume, or metric cardinality, even if they don't say "cost" or "optimize" explicitly.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Comprehensive documentation guide for Golang projects, covering godoc comments, README, CONTRIBUTING, CHANGELOG, Go Playground, Example tests, API docs, and llms.txt. Use when writing or reviewing doc comments, documentation, adding code examples, setting up doc sites, or discussing documentation best practices. Triggers for both libraries and applications/CLIs.
A curated, installable collection of Claude Code agent skills covering development, writing, productivity, and knowledge management workflows.
Dimensionality reduction in very large datasets using Siamese Networks
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.
A collection of opinionated agent skills for Claude Code, including sparring, design, planning, and auditing workflows.
17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimizing observability costs.
>-
Analyzes cloud infrastructure and architectures to identify wasted spend and right-sizing opportunities.
Build PFC 5.0 asphalt-mixture specimens with explicit aggregate objects, a declared homogenized-mastic or fine-particle abstraction, residual air voids, measured gradation conversion, contact-pair assignment, compaction, equilibrium, and mass-volume closure; use before Marshall, rutting, creep, or strength tests.
Investigate and reduce SigNoz telemetry ingestion cost and metric cardinality across metrics, logs, and traces. Find what drives SigNoz spend (via the Cost Meter), which metrics have runaway or unbounded label cardinality, and safe, dashboard-, alert-, and Infra-page-aware ways to cut volume. Make sure to use this skill whenever the user asks "why is my SigNoz bill so high", "what's driving my ingestion cost", "reduce telemetry volume", "which metrics cost the most", "cardinality health check", or "what can I safely drop" — or otherwise asks about telemetry spend, ingestion volume, or metric cardinality, even if they don't say "cost" or "optimize" explicitly.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Comprehensive documentation guide for Golang projects, covering godoc comments, README, CONTRIBUTING, CHANGELOG, Go Playground, Example tests, API docs, and llms.txt. Use when writing or reviewing doc comments, documentation, adding code examples, setting up doc sites, or discussing documentation best practices. Triggers for both libraries and applications/CLIs.
A curated, installable collection of Claude Code agent skills covering development, writing, productivity, and knowledge management workflows.
Dimensionality reduction in very large datasets using Siamese Networks
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.
A collection of opinionated agent skills for Claude Code, including sparring, design, planning, and auditing workflows.
17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimizing observability costs.
>-
Analyzes cloud infrastructure and architectures to identify wasted spend and right-sizing opportunities.
Build PFC 5.0 asphalt-mixture specimens with explicit aggregate objects, a declared homogenized-mastic or fine-particle abstraction, residual air voids, measured gradation conversion, contact-pair assignment, compaction, equilibrium, and mass-volume closure; use before Marshall, rutting, creep, or strength tests.
Investigate and reduce SigNoz telemetry ingestion cost and metric cardinality across metrics, logs, and traces. Find what drives SigNoz spend (via the Cost Meter), which metrics have runaway or unbounded label cardinality, and safe, dashboard-, alert-, and Infra-page-aware ways to cut volume. Make sure to use this skill whenever the user asks "why is my SigNoz bill so high", "what's driving my ingestion cost", "reduce telemetry volume", "which metrics cost the most", "cardinality health check", or "what can I safely drop" — or otherwise asks about telemetry spend, ingestion volume, or metric cardinality, even if they don't say "cost" or "optimize" explicitly.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Comprehensive documentation guide for Golang projects, covering godoc comments, README, CONTRIBUTING, CHANGELOG, Go Playground, Example tests, API docs, and llms.txt. Use when writing or reviewing doc comments, documentation, adding code examples, setting up doc sites, or discussing documentation best practices. Triggers for both libraries and applications/CLIs.
A curated, installable collection of Claude Code agent skills covering development, writing, productivity, and knowledge management workflows.
Dimensionality reduction in very large datasets using Siamese Networks
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.
A collection of opinionated agent skills for Claude Code, including sparring, design, planning, and auditing workflows.
17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimizing observability costs.
>-
Analyzes cloud infrastructure and architectures to identify wasted spend and right-sizing opportunities.
Build PFC 5.0 asphalt-mixture specimens with explicit aggregate objects, a declared homogenized-mastic or fine-particle abstraction, residual air voids, measured gradation conversion, contact-pair assignment, compaction, equilibrium, and mass-volume closure; use before Marshall, rutting, creep, or strength tests.
Investigate and reduce SigNoz telemetry ingestion cost and metric cardinality across metrics, logs, and traces. Find what drives SigNoz spend (via the Cost Meter), which metrics have runaway or unbounded label cardinality, and safe, dashboard-, alert-, and Infra-page-aware ways to cut volume. Make sure to use this skill whenever the user asks "why is my SigNoz bill so high", "what's driving my ingestion cost", "reduce telemetry volume", "which metrics cost the most", "cardinality health check", or "what can I safely drop" — or otherwise asks about telemetry spend, ingestion volume, or metric cardinality, even if they don't say "cost" or "optimize" explicitly.