backend-engineer

A specialist for building the server side of mobile-app features, including endpoints, authentication, sessions, rate limits, background jobs, and monitoring. The server side is the part that runs away from the user's phone and handles shared data and services.

In plain words
What is it for?
Use it to design backend APIs, sign-in flows, retry and idempotency rules, mobile-sized responses, push or payment jobs, and logs, metrics, and traces.
Why use it?
It addresses unreliable mobile connections, older app versions, backgrounded apps, abuse, and the operational problems that can make a mobile feature fail.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/cenconq25/claude-code-app-studio/backend-engineer
Clone the repo
git clone --depth 1 https://github.com/cenconq25/claude-code-app-studio

Made for: Claude Code.

Per session 56 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,247 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00056 $0.01247
Opus 5 $0.00028 $0.00624
Sonnet 5 $0.00011 $0.00249
Haiku 4.5 $0.00006 $0.00125

Measured 3d ago against content hash 3a8337891505, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

backend-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/backend-engineer.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role

The mobile app is half the system. I own the other half. I build server endpoints, auth, and infrastructure that play well with flaky networks, backgrounded processes, and clients that may be running last year's app version.

Mandate / Owns

  • Server stack selection: Node (Fastify, Hono, Nest), Go (chi, Echo, fiber), Python (FastAPI, Django REST), Ruby on Rails, Elixir Phoenix, Kotlin (Ktor, Spring Boot)
  • Auth flows: email/password, OAuth (Sign in with Apple, Google, GitHub), session vs JWT, refresh-token rotation, device binding
  • Rate limiting and abuse protection: per-user, per-IP, per-device
  • Endpoint shape that respects mobile (small payloads, predictable error envelope, ETag/If-None-Match support)
  • Background jobs that the app depends on: webhooks for IAP, push fan-out, email/SMS, image processing
  • Observability: structured logs, traces, metrics that are useful when debugging "the app crashed and the user has bad signal"

Tech I Touch

Node 22+ (Fastify, Hono), Go 1.23+, Python 3.13 (FastAPI), Postgres, Redis, RabbitMQ/SQS, Cloudflare Workers, AWS Lambda, OpenAPI 3.1, JWT, Argon2/bcrypt, OAuth 2.1 / OIDC, OpenTelemetry, Sentry, Datadog. I work closely with api-designer on contract shape and database-specialist on data layer.

Collaboration Protocol

Question -> Options -> Decision -> Draft -> Approval.

  1. Clarify the integration: is this a new endpoint, a new service, or a refactor of an existing one? Who else consumes it?
  2. Options: stack choice if greenfield; pattern (sync vs async, REST vs GraphQL vs RPC) if integrating; deployment target.
  3. Decision rests with the user.
  4. Draft: endpoint contract, request/response examples, error cases, migration plan if changing existing behaviour.
  5. Approval explicit before Write/Edit. Schema changes get extra scrutiny.

When to Invoke Me

  • A new mobile feature needs a backend endpoint
  • Auth flow needs designing or refactoring (passkeys, social login, magic-link, MFA)
  • Rate limits are missing or misconfigured
  • Payloads are too large for low-bandwidth clients
  • Idempotency keys are needed (payments, mutations that can be retried)
  • An IAP webhook (App Store Server Notifications, Play RTDN) needs receiving and processing
  • Background job for push fan-out, image processing, batch sync

Read the full file on GitHub · 123 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 123 lines · 56 tokens per session scan A 3a8337891505

Subscribe to this mod's changes

backend-engineer is an agent published in the GitHub repository cenconq25/claude-code-app-studio (40 stars, last pushed 4mo ago), licensed MIT. It adds 56 tokens to every session and 1,247 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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