* feat(skill): cross-pollinate the new tool wave into catalog routing Wire the recent tool skill wave into the two-layer routing graph so the new tool skills are reachable from the methodology skills that own their domains, and vice versa: - methodology -> tool down-routes: platform-engineering -> kubernetes, terraform, telemetry, postgres, grafana; site-reliability-engineering -> telemetry, grafana; data-engineering and backend-engineering -> postgres; frontend-engineering -> mobile-development; verification-methodology -> playwright, documents; technical-documentation -> documents - neckbeard: add mobile-development and documents routing rows plus change-surface coverage entries, and cross-link the lightweight test-hardening path to qa-methodology's bounded mutation-review material - collaboration layer: chief-of-staff-methodology -> slack/notion/email, go-to-market -> crm, conditional-customer-success -> crm; fix the dead seo-content-optimization reference in go-to-market (now seo-audit) - references/skill-triggers.md: add trigger rows for the 14 new skills - bring go-to-market's description up to the quality validator's imperative-verb + negative-boundary requirement and regenerate catalogs Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> * fix(skill): add eval manifest for technical-documentation The eval-coverage ratchet fails on modified skills without a schema-valid manifest once coverage passes 50%. technical-documentation was modified by the routing cross-pollination change and lacked one; add six output-quality cases covering README authorship, API reference generation, CLI help design, agent-facing docs, documentation-site IA, and troubleshooting sections. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> --------- Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Backend Engineering
Backend engineering methodology — API implementation patterns (REST, gRPC, GraphQL), service architecture (clean/hexagonal/layered), database access patterns, integration and middleware design, error handling, and service-level testing. Language and framework agnostic.
Why Install This Skill
Your agent gains structured patterns for API design, service architecture, database access, error handling, and integration — instead of improvising each time. Fillable templates turn service designs and error contracts into reviewable records, and the bundled N+1 query spotter catches a whole class of database performance bugs during review.
What You Get
| Directory | Purpose |
|---|---|
SKILL.md |
Core methodology, trigger conditions, reference index |
references/ |
Deep-dive reference files loaded on demand |
templates/ |
Fillable records: service design record, error-handling taxonomy |
scripts/ |
n1-query-spotter.py — scans Python source for potential N+1 query patterns |
evals/ |
Output-quality eval manifest for the skill's methodology cases |
Triggers
Building or reviewing APIs, designing service layers, implementing database access patterns, adding error handling, or integrating external services.
Requirements
Platform-agnostic. Applicable to any language/framework stack. The bundled script needs only Python 3 (standard library).
Quick Start
Scan a service for potential N+1 query patterns before a performance review:
python3 backend-engineering/scripts/n1-query-spotter.py services/orders.py
Each finding points at the query call, the enclosing loop, and whether the loop variable is used in the query (high confidence vs possible). Add --json for machine-readable output, and run it from CI — the script exits 1 when findings exist.
Load SKILL.md for the methodology overview and reference table, then load specific references as needed for the task at hand.