Skills — Index

Routing map for AI agents. Find the entry whose "reach for it when" matches the task in
front of you, then fetch that article — append .md to any link for the raw markdown source
(e.g. /wiki/push-compute-to-datastore.md). Every skill leads with when to use it and is dense
with copy-paste patterns and "do X not Y because Z" rules.

Keep this index current: whenever a skill article is added, renamed, or re-scoped, update the
matching line here so this stays the single place an agent looks first.

Databases & backend performance

Start at Push Compute to the Datastore — the hub and
decision ladder; the five below are its deep dives.

• Push Compute to the Datastore — reach for it when
  deciding where computation should live (app vs Postgres vs Redis), killing an N+1 or an
  app-side loop, fixing slow OFFSET pagination, or adding aggregation / ranking / queues /
  rate-limiting / caching. The ladder: constraints → indexes → set-based SQL → DB engines →
  Redis → app code → a specialized store.
• Postgres Full-Text & Fuzzy Search — reach for it when
  building a search box, autocomplete, typo tolerance, relevance ranking, or hybrid
  keyword+vector search — or deciding native FTS vs Elasticsearch. Covers tsvector,
  websearch_to_tsquery, ts_rank_cd, GIN/GiST/RUM, pg_trgm, RRF hybrid search, ParadeDB.
• Postgres Query Planning & EXPLAIN — reach for it when a
  query is slow and you need to know why: reading EXPLAIN (ANALYZE, BUFFERS), fixing bad
  row estimates / extended statistics, work_mem spills, the prepared-statement generic-plan
  trap.
• Postgres Concurrency, MVCC & Throughput —
  reach for it when diagnosing bloat / vacuum, lock waits and deadlocks, "too many
  connections" / pooling, isolation or race bugs, a slow bulk load (COPY/unnest), or making
  a write idempotent.
• Postgres Scale-Out, Replication & Data Movement — reach for it
  when one box isn't enough: read replicas & read-your-writes, Citus sharding, CDC / outbox,
  partition-detach archival, denormalization, HA / failover.
• Redis Internals & Datastore Selection —
  reach for it when going deeper on Redis (memory/encoding, Cluster, Bloom/Count-Min/Top-K/
  t-digest) or deciding whether to add a specialized store (search engine, ClickHouse/OLAP,
  Kafka, graph, vector DB) instead of stretching Postgres/Redis.

Deploy & operations

• Kamal Auto-Versioning — reach for it when versioning a
  Kamal-deployed app: auto-bump semver from Conventional Commits, pre/post-deploy hooks, tag
  the release on a healthy deploy, embed the version in a Go binary (svu, ldflags).
• Rails Production Playbook — reach for it when running
  Rails in production and want boring, explicit, deny-by-default, observable conventions.

Language & framework engineering

• Sandi Metz' Rules — reach for it when you want OO design
  guard-rails: keep classes/methods small, focused, replaceable (Ruby/Rails; the principles
  travel).
• React: Rules & Project Structure (2026) — reach for it when
  starting or structuring a React frontend: the 2026 stack (TanStack, shadcn/Tailwind v4,
  feature-based layout, query patterns).
• Scaling Rails: Vertical & Horizontal — reach for it when scaling a
  Rails app to the next measured bottleneck (Puma/GVL, the database, jobs, caching).

Working with AI agents (methodology)

• Getting Started with Agentic Engineering —
  start here for how to build software with AI agents on these projects.
• Agentic Engineering — the working methodology; specs are the
  source of truth, code is a build artifact.
• The Agentic-Feature Workflow — reach for it when running
  a feature through specify → clarify → plan → tasks → implement → verify → retrospective.
• Spec-Driven Workflow — reach for it when you need the plan
  to be the contract before any code is written.
• Model Routing: Haiku, Sonnet, Opus — reach for it
  when deciding which model tier a task should run on.
• Subagents and Context Injection — reach for it
  when designing subagent prompts: hand the map down, pre-fetch context, don't let agents
  rediscover it.
• Trust but Verify — reach for it when setting up an independent
  adversarial review gate between implementation and deploy.
• The Compounding Layer — reach for it when capturing
  learnings: feed lessons back as constitution rules + extracted skills.

When an agent run goes wrong (failure modes)

• The Illusion of Speed — fast generation, slow discovery/
  diagnosis/fixing. Fix with decomposition and oversight.
• The One-Shot Problem — a task too big for one prompt silently
  drops requirements. Fix by decomposing into one-shottable pieces.
• Losing Control: When the Agent Goes Off-Plan
  — scope creep, hallucination, premature execution. The plan is the contract.

Starting a new project

• New Project — References — reach for it when bootstrapping a new
  repo: the methodology, skills, and playbooks to pull in and reference.