Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review
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Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review
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Stars23,060
Forks3,139
LanguagePython
LicenseMIT
๐ฆ Ships with claude-skills
</> SKILL.md
senior-backend.SKILL.md
---name: "senior-backend"
description: Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Covers Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.
---# Senior Backend Engineer
Backend development patterns, API design, database optimization, and security practices.
---## Quick Start
```bash
# Generate API routes from OpenAPI spec
python scripts/api_scaffolder.py openapi.yaml --framework express --output src/routes/
# Analyze database schema and generate migrations
python scripts/database_migration_tool.py --connection postgres://localhost/mydb --analyze
# Load test an API endpoint
python scripts/api_load_tester.py https://api.example.com/users --concurrency 50 --duration 30
```
---## Tools Overview
### 1. API Scaffolder
Generates API route handlers, middleware, and OpenAPI specifications from schema definitions.
## Assumptions and Verifiable Success Criteria (Karpathy discipline)
Before this skill scaffolds, recommends a pattern, or modifies a schema, the following four assumptions MUST be surfaced. If any are unknown, the skill stops and walks the [Forcing-question library](#forcing-question-library-matt-pocock-grill) instead.
1. **Read/write ratio + one-year p99 QPS** โ drives DB, cache, queue, and partitioning choices. Kleppmann, *DDIA* (2017).
4. **SLO + named error-budget consumer** โ Google SRE Workbook canon. No SLO = no reliability work prioritization.
**Verifiable success criteria** (Karpathy #4) โ every recommendation this skill emits must include:
- Latency targets (p50, p95, p99 in ms)
- Uptime / SLO target
- RPO + RTO
If any of those three is not stated, the recommendation is incomplete โ return to Q7 of the forcing-question library.
The `scripts/backend_decision_engine.py` tool encodes these checks: it refuses to recommend a profile without read/write ratio + QPS + tenancy + data sensitivity + pattern preference.
---
## Customization profiles
Four built-in profiles in `profiles/` calibrate every recommendation:
| Profile | When to pick | Pattern | Latency floor (p99) |
The tool returns the best-fit profile, runner-up tradeoff (if within 15%), stack picks, anti-patterns, named approvers, and SLO floor. **This tool never auto-approves.**
To add a custom profile: copy `profiles/node-express.json` to `profiles/<your-org>.json` and adjust `constraints` + `success_thresholds` + `named_approver_chain`.
---
## Composition map
This skill does NOT reimplement scope owned by the POWERFUL-tier specialists. It forks into them. See `references/composition_map.md` for the full routing table. Key forks:
| Concern | Fork into |
|---|---|
| API contract / breaking-change risk | `engineering/skills/api-design-reviewer/` |
The `cs-backend-engineer` agent orchestrates these forks via `context: fork`. Invoke it from another agent with `Agent({subagent_type: "cs-backend-engineer", prompt: "..."})` or via `/cs:backend-review <your problem>`.
---
## Forcing-question library (Matt Pocock grill)
Before locking any backend decision, walk the seven forcing questions in `references/forcing_questions.md`. Discipline:
1. One question per turn. No bundling.
2. Always recommend the answer with cited canon.
3. Track answers in `/tmp/backend-grill-<date>.md`.
4. If a kill criterion trips, stop. Don't scaffold around an unresolved gap.
5. After Q7, run `backend_decision_engine.py` with the seven answers.