Individual skill

ddia-principles

Designing Data-Intensive Applications (DDIA) distilled reference guide by Martin Kleppmann. MUST be loaded when: designing database schemas, choosing storage engines, implementing replication or partitioning, handling distributed transactions, building batch/stream processing pipelines, choosing consistency models, implementing consensus, designing data flow architectures, evaluating trade-offs between availability and consistency, encoding/serialization decisions, data modeling (relational vs document vs graph), building fault-tolerant systems, or any system design and architecture discussion involving data-intensive applications. Trigger on: database design, replication, partitioning, sharding, transactions, isolation levels, consistency, consensus, CAP theorem, batch processing, stream processing, MapReduce, Kafka, event sourcing, CDC, OLTP, OLAP, B-tree, LSM-tree, data warehouse, schema evolution, encoding formats, distributed systems, fault tolerance, leader election, quorum.

ddia-principles/SKILL.md

Source commit 27db986fd2790ad1a1818a7f1b2c5d91b3843b8e

What was checked

Matches the observed repository HEAD

Yes

Scanner rules are current

Yes

Repository scan complete

No

Skill scan complete

No

Observed behavior

Instructions only

Last checked

Nov 6, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.