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Magnus HedemarkandGitHub
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Add outbox/inbox implementation, idempotent message handling, migration coexistence seams, evals, and exact specialist routing.\n\nAI-assisted: Jasper orchestrated implementation and verification with OpenCode. Signed-off-by: Magnus Hedemark <magnus919@pm.me>
40 lines
2.4 KiB
Markdown
40 lines
2.4 KiB
Markdown
# Backend Engineering
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Backend engineering methodology — API implementation patterns (REST, gRPC, GraphQL), service architecture (clean/hexagonal/layered), event-driven application flows, outbox/inbox coordination, migration coexistence seams, database access patterns, integration and middleware design, error handling, and service-level testing. Language and framework agnostic.
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## Why Install This Skill
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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.
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## What You Get
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| Directory | Purpose |
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|-----------|---------|
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| `SKILL.md` | Core methodology, trigger conditions, reference index |
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| `references/` | Deep-dive reference files loaded on demand |
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| `templates/` | Fillable records: service design, event flow/coexistence, and error-handling taxonomy |
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| `scripts/` | `n1-query-spotter.py` — scans Python source for potential N+1 query patterns |
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| `evals/` | Output-quality eval manifest for the skill's methodology cases |
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## Triggers
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Building or reviewing APIs, designing service layers, implementing database access patterns, adding error handling, integrating external services, publishing or consuming domain events, implementing outbox/inbox delivery, or keeping old and new service paths safe during a migration.
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Do not load this skill as the owner of API/event contracts, service decomposition strategy, schema/pipeline operations, or cross-system migration lifecycle; route those decisions to the linked specialist skills.
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## Requirements
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Platform-agnostic. Applicable to any language/framework stack. The bundled script needs only Python 3 (standard library).
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## Quick Start
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Scan a service for potential N+1 query patterns before a performance review:
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```bash
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python3 backend-engineering/scripts/n1-query-spotter.py services/orders.py
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```
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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.
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Load SKILL.md for the methodology overview and reference table, then load specific references as needed for the task at hand.
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