AI-Agents-Orchestrator: Agent for Claude Code

.claude/agents/backend-api.md

backend-api is an agent for Claude Code from hoangsonww/AI-Agents-Orchestrator. It costs 21 tokens per session (956 once invoked), scanned A, original, MIT.

A backend development specialist for the server-side parts of software, including APIs, databases, and services that communicate with other applications. It covers REST, GraphQL, gRPC, several programming languages, and common database systems.

In plain words
What is it for?
Use it to build or review APIs, database integrations, microservices, server endpoints, data validation, and backend architecture in the listed technologies.
Why use it?
It helps turn application requirements into server code and architecture without having to work out API design, data storage, validation, and service communication separately.

Agent for Claude Code

Written for Claude Code: installed under .claude/.

This is hoangsonww/AI-Agents-Orchestrator's own configuration. It tells Claude Code how to work on AI-Agents-Orchestrator itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AI-Agents-Orchestrator configures →

Reuse

Borrowing it

Nothing to install: this file belongs to hoangsonww/AI-Agents-Orchestrator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/hoangsonww/AI-Agents-Orchestrator/main/.claude/agents/backend-api.md
Clone the repo
git clone --depth 1 https://github.com/hoangsonww/AI-Agents-Orchestrator

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for backend-api

README.md
[![agentmods](https://agentmods.dev/badge/agents/hoangsonww/ai-agents-orchestrator/backend-api.svg)](https://agentmods.dev/agents/hoangsonww/ai-agents-orchestrator/backend-api)
Your own site
<a href="https://agentmods.dev/agents/hoangsonww/ai-agents-orchestrator/backend-api"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-agents-orchestrator/backend-api.svg" alt="Measured on agentmods" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 956 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 5.1 $0.00021 $0.00956
Opus 5 $0.00010 $0.00478
Sonnet 5 $0.00004 $0.00191
Haiku 4.5 $0.00002 $0.00096

Measured 6d ago against content hash db05903ff31a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

backend-api 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 6d 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-api.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior backend engineer specializing in API design and server-side development for the AI Coding Tools Orchestrator project.

Core Expertise

API Design

  • REST: Resource modeling, HATEOAS, versioning strategies
  • GraphQL: Schema design, resolvers, subscriptions, federation
  • gRPC: Protocol buffers, streaming, service mesh
  • OpenAPI/Swagger: Specification writing, code generation

Frameworks

  • Python: FastAPI, Flask, Django, aiohttp
  • Node.js: Express, NestJS, Fastify
  • Go: Gin, Echo, Chi

Database Integration

  • SQL: PostgreSQL, MySQL, SQLite
  • NoSQL: MongoDB, Redis, DynamoDB
  • ORMs: SQLAlchemy, Prisma, TypeORM
  • Query optimization: Indexes, explain plans, N+1 prevention

Architecture Patterns

  • Microservices and monolith-first
  • Event-driven architecture
  • CQRS and Event Sourcing
  • Domain-Driven Design (DDD)

Project-Specific Guidelines

This project uses:

  1. Flask: For UI endpoints in orchestrator/ui/app.py and agentic_team/ui/app.py
  2. FastMCP: For MCP server in mcp_server/server.py
  3. httpx: For HTTP client operations (not requests)
  4. Pydantic: For data validation and serialization
  5. SQLite: For graph context storage in orchestrator/context/

Error Handling Pattern

from dataclasses import dataclass
from typing import Optional

@dataclass
class APIResponse:
    success: bool
    data: Optional[dict] = None
    error: Optional[str] = None
    error_code: Optional[str] = None

# Never raise exceptions from API endpoints - return error responses
def handle_request(request_data: dict) -> APIResponse:
    try:
        result = process_data(request_data)
        return APIResponse(success=True, data=result)
    except ValidationError as e:
        return APIResponse(success=False, error=str(e), error_code="VALIDATION_ERROR")
    except Exception as e:
        logger.exception("Unexpected error")
        return APIResponse(success=False, error="Internal error", error_code="INTERNAL_ERROR")

Read the full file on GitHub · 133 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. 6d ago First seen · 133 lines · 21 tokens per session scan A db05903ff31a

Subscribe to this mod's changes

backend-api is an agent published in the GitHub repository hoangsonww/AI-Agents-Orchestrator (84 stars, last pushed 20d ago), licensed MIT. It adds 21 tokens to every session and 956 once invoked, about $0.0001 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.

Related

Other agents, from other repositories

event-sourcing-architect

Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries.

wshobson/agents · 60 tokens

backend-engineer

Use when creating or modifying backend code: API routes, use cases, domain models, repositories, infrastructure services, or dependency injection configuration. Follows Hexagonal Architecture, DDD, and DIOD conventions.

CodelyTV/agentic_programming-course · 45 tokens

clawteam-rnd-backend

Backend R&D task agent — layered abstraction, defensive coding, consistency-first data, built-in observability, evolvable design, perf/resource awareness; architecture layers, quality trade-offs, error taxonomy, distributed consistency patterns.

deepelementlab/jupyter-studio · 52 tokens

clawteam-system-architect

System architect task agent — layered abstraction, separation of concerns, evolvable design, NFR-driven, contract-first APIs, explicit trade-offs; multi-view architecture, style matrix, interface principles, ADR-style decisions; DDD, data, resilience, evolution.

deepelementlab/jupyter-studio · 59 tokens

database-engineer

Use when creating or modifying database schemas, migrations, or SQL scripts. Follows PostgreSQL conventions: NOT NULL for required fields, plural table naming, and TEXT with CHECK constraints over VARCHAR/CHAR.

CodelyTV/agentic_programming-course · 44 tokens

power-platform-expert

Power Platform expert providing guidance on Code Apps, canvas apps, Dataverse, connectors, and Power Platform best practices.

asleekgeek/claude-multiagent-catalogue · 28 tokens