data-report
openbooklet.com/s/data-reportopenbooklet.com/s/[email protected]GET /api/v1/skills/data-reportæ CSV/Excel/JSON æ°æ®è½¬ææ¼äº®çå¯è§åæ¥å页
Substack / Medium é«çº§æé¿ææç, éåå ¬ä¼å·ãå客åå¸
æ¶è´¹æé 对仪表æ¿: ä¿¡å· ticker + KPI + 30 天æ±ç¶ + è¶å¿
奶油纸 + é红 + èå¾ç½æ ¼ mask + é»è¾¹ç¡¬å¡ç + pipeline ç
æ纸èæ¯ + Playfair, 左侧å¦ä¹ ç®æ 常驻, å« MCQ èªæµé¡µ
8 页åè²èæ¯, 160px display + 4px accent + Mono ç®å¤´å表
æ·±å¤æ¸å + æ¼æµ® orbs + SVG å导åå¾è°± + JetBrains Mono
é»åº + CRT ç½æ ¼æ«æ线 + $ å½ä»¤è¡æ é¢ + èè·ç»¿å¤§å + ä¸æ¡£ tag
çµåæå¿ Ã çµå墨水é£, WebGL æµä½èæ¯ + 衬线 display
GitHub-dark + ç´«èç¯å¢å + ä¸è²æ¸åæ é¢ + GitHub é£ä»£ç
éæ» 1920Ã1080 ç»å¸, React ç»ä»¶çº§èªç±ç»å, ä¸ç»æ¨¡æ¿
10 页èèµ deck, ç½åº + èç´«æ¸å hero, traction æ±ç¶, $X.XM ask
tokyo-night é»è®¤ä¸»é¢, T åæ¢ 5 主é¢, S æå¼æè¯å¨ popup
æ hero + 亮å 容, æ©âæ¡ accent, ç¹æ§å¡ + å®ä»· + CTA
Replit Slides å «å¥ä¸»é¢ (helix/holm/vance/bevel/world/atlas/bluehouse)
红ç¥çè¦ç¤ºè² + hazard æ¡çº¹ + L1/L2/L3 tier å¡ç + å é¤çº¿æ é¢
GitHub-dark + JetBrains Mono + ç»ç«¯ä»£ç å, å« agenda + Q&A
å¥¶æ²¹åº + æå blob + 马å¡é¾åè§å¡ç + Playfair æä½åºå·
9 页 3:4 ç«çå¾æ, æ pastel + è线 sticker å¡ç
çº¯ç½ + 顶é¨å½©è¹ bar + æ¸åæå + 马å¡é¾è½¯å¡ç + é»åº pill
两页跨页çµåæå, å°é¢ + 课ç¨é¡µ + pull-quote + æ¥éª¤å表
Auto-indexed from nexu-io/html-anything
Are you the author? Claim this skill to take ownership and manage it.
Related Skills
x-twitter-scraper
X (Twitter) data platform skill â tweet search, user lookup, follower extraction, engagement metrics, giveaway draws, monitoring, webhooks, 19 extraction tools, MCP server.
analytics-engineering
Use this skill when building dbt models, designing semantic layers, defining metrics, creating self-serve analytics, or structuring a data warehouse for analyst consumption. Triggers on dbt project setup, model layering (staging, intermediate, marts), ref() and source() usage, YAML schema definitions, metrics definitions, semantic layer configuration, dimensional modeling, slowly changing dimensions, data testing, and any task requiring analytics engineering best practices.
Database Schema Reviewer
Reviews database schemas for normalization issues, missing indexes, naming inconsistencies, and scalability risks.
data-pipelines
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
data-quality
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
real-time-streaming
Use this skill when building real-time data pipelines, stream processing jobs, or change data capture systems. Triggers on tasks involving Apache Kafka (producers, consumers, topics, partitions, consumer groups, Connect, Streams), Apache Flink (DataStream API, windowing, checkpointing, stateful processing), event sourcing implementations, CDC with Debezium, stream processing patterns (windowing, watermarks, exactly-once semantics), and any pipeline that processes unbounded data in motion rather than data at rest.