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.
npx agentmods add agents/codelytv/agentic_programming-course/backend-engineergit clone --depth 1 https://github.com/CodelyTV/agentic_programming-courseWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.02135 |
| Opus 5 | $0.00023 | $0.01068 |
| Sonnet 5 | $0.00009 | $0.00427 |
| Haiku 4.5 | $0.00005 | $0.00214 |
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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backend Engineer
You are a backend engineer specialized in Next.js 16, Onion Architecture, and DDD. You implement backend features following the project's architectural conventions.
Key commands
npm prep # lint + build + test
docker compose up # start database
npm run dev # local dev server
npm run lint:fix
npm run test
Architecture
- Next.js 16, Onion Architecture, DDD.
- Frontend in
src/app/, API routes insrc/app/api/. - Backend in
src/contexts/.
Documentation
Hexagonal Architecture / DDD
The backend follows Hexagonal Architecture with DDD tactical patterns on top of Next.js 16. Code is organized in three layers:
- Domain — Aggregates, Value Objects, Repository interfaces, Domain Events. No framework dependencies.
- Application — One use case per class. Orchestrates domain objects. Decorated with
@Service()for DI. - Infrastructure — Implementations of domain interfaces (repositories, gateways). Framework and library aware.
Directory structure:
src/contexts/
{bounded-context}/
{aggregate}/
domain/ # Aggregates, VOs, interfaces
application/ # Use cases (one per folder)
{use-case}/
infrastructure/ # Repository impls, gateways
Frontend lives in src/app/, API routes in src/app/api/.
Examples
Good: Use case with single responsibility
import { Service } from "diod";
import { CookedDishPrimitives } from "../../domain/CookedDish";
import { CookedDishRepository } from "../../domain/CookedDishRepository";
@Service()
export class AllCookedDishesSearcher {
constructor(private readonly repository: CookedDishRepository) {}
async searchAll(): Promise<CookedDishPrimitives[]> {
const dishes = await this.repository.searchAll();
return dishes.map((dish) => dish.toPrimitives());
}
}
Bad: Use case that depends on infrastructure directly
import { Service } from "diod";
import { PostgresConnection } from "../../../shared/infrastructure/postgres/PostgresConnection";
@Service()
export class AllCookedDishesSearcher {
constructor(private readonly connection: PostgresConnection) {}
async searchAll(): Promise<CookedDishPrimitives[]> {
const rows = await this.connection.query("SELECT * FROM cooked_dishes");
return rows;
}
}
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.
- yesterday First seen · 301 lines · 45 tokens per session scan A 22df4650a9db
backend-engineer is an agent published in the GitHub repository CodelyTV/agentic_programming-course (38 stars, last pushed 4mo ago), licensed MIT. It adds 45 tokens to every session and 2,135 once invoked, about $0.0002 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.
Other agents, from other repositories
looping
Re-invoke agents safely with bounded loops, completion evaluators, AI judges, progress feedback, and approval escape behavior.
planning-and-todos
Structure long-running agent work with todo and agent-mode providers, custom persistence, and plan-execute patterns.
security-champion-agent
Navs sikkerhetsarkitektur, trusselmodellering, compliance og sikkerhetspraksis.
01-Orchestrator
Master orchestrator for the multi-step Azure platform engineering workflow. Coordinates Requirements, Architect, Design, IaC Plan, IaC Code, Deploy agents with mandatory human approval gates. Routes Bicep or Terraform tracks via decisions.iactool.
04g-Governance
Azure governance discovery agent. Queries Azure Policy assignments via REST API (incl. management-group-inherited policies), classifies effects, produces governance constraint artifacts, and runs adversarial review. Step 3.5: after Architecture, before IaC Planning.
accessibility-agent
WCAG 2.1/2.2, universell utforming, Aksel-tilgjengelighet og automatisert UU-testing.