Claude Code craft for working engineers: authoring Agent Skills (the library's own standard), prompt engineering with the injection-defense doctrine, git/code review with run-verified agent traps, the Board of Advisors multi-agent code review (board-review + five specialist subagents and a chair), defect-epidemiology (treat a confirmed bug as evidence about a population), rule-stress-testing, software-archaeology, Comrade Engineer's pencil pass, The Foreman's draw inspection, the Creative Workaround Genius (another route when the obvious one fails, never around a control), the project-manager subagent with its skill for multi-session and multi-agent work (requirement ledger, token budget, exhaustive QC sweep), Puppet Master (the whole job on the fewest tokens with no loss of quality: fewer turns, small new context, a transcript audit), and Chicken Little (Aether) — the multi-domain persona with forward-deployed advisor and compiler autopsy modes.
13 skills · 7 agents
Decision discipline under uncertainty: pre-mortem (with the counsel rail), tabletop wargaming and no-win drills under full exercise control, weak-signal navigation with cue-graded confidence, Bayesian updating via natural frequencies, reference-class forecasting, competing hypotheses analysis, minority-report dissent capture, the Rashomon-effect protocol for conflicting recollections, and The Challenger.
10 skills
Full-stack application development with a lean-code philosophy: architecture, FastAPI backends, databases/ORM, modern dynamic frontends, realtime features, ML in production, testing strategy, deployment, and evidence-based UI/UX inspection with severity-rated findings and human-factors instruments (Fitts, NASA-TLX).
10 skills
The improvement methods with teeth: DMAIC with a fully worked control-chart project (provisional-limits discipline included), FMEA with the evidence-gated Action Priority table, measurement systems analysis extended to LLM-as-judge gauge studies, design of experiments, evolutionary operation (EVOP), root cause analysis, and the project command center doctrine.
7 skills
Statistical inference done honestly, causal inference (DAGs, DiD/IV/RDD), A/B test design (SRM, peeking, MDE, variance reduction), survey and sampling design (total survey error, nonresponse), spreadsheet modeling discipline, and assertion-evidence presentations with a build-and-lint toolchain.
6 skills
Applied machine learning with honest evaluation: project framing (the leanest model is no model), supervised modeling, feature engineering, model evaluation (threshold as a fitted parameter), time-series forecasting with horizon-aware backtest sizing and measured interval coverage, and anomaly detection with the degenerate-case floor.
6 skills