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 skills add vasilyu1983/AI-Agents-public --skill software-backendgit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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.
[](https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-backend)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-backend"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-backend/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-backend"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-backend.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.03259 |
| Opus 5 | $0.00020 | $0.01630 |
| Sonnet 5 | $0.00008 | $0.00652 |
| Haiku 4.5 | $0.00004 | $0.00326 |
Grade A, and why
software-backend 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Backend Engineering
Use this skill for backend service implementation and review: API boundaries, auth, data access, jobs, caching, observability, and production hardening. If the main question is platform selection, system topology, or API-contract design without implementation, hand off early.
Defaults
When this skill is active, prefer these defaults unless the repo or user says otherwise:
- validate at the boundary and keep types explicit
- use PostgreSQL plus pooling for relational workloads
- use structured logs, OpenTelemetry, explicit timeouts, and rate limits
- make mutations idempotent and background work retry-safe
- use RFC 9457 Problem Details for machine-readable errors
Quick Reference
| Need | Default Direction |
|---|---|
| Public HTTP API | REST with explicit contracts and timeouts |
| Internal TS monorepo API | tRPC when end-to-end type safety matters |
| High-throughput internal RPC | Connect or gRPC |
| Complex client-shaped reads | GraphQL |
| Relational data | PostgreSQL with migrations and pooling |
| Background work | Queue plus idempotent handlers and DLQ policy |
| Browser auth | OIDC or OAuth plus httpOnly cookies |
| Service auth | short-lived tokens, workload identity, or signed service credentials |
| Caching | explicit TTLs and invalidation rules |
| Observability | correlation IDs, traces, structured logs, saturation metrics |
When to Use This Skill
- building or reviewing REST, GraphQL, tRPC, Connect, or gRPC services
- implementing auth, validation, rate limits, caching, queues, or webhook handling
- modelling schemas and running safe migrations
- hardening service behavior for retries, timeouts, and observability
- scaffolding or refactoring a backend with production defaults
Route Elsewhere
- frontend-only work -> software-frontend
- infrastructure provisioning and cluster design -> ops-devops-platform
- API contract design without implementation -> dev-api-design
- BaaS platform selection (data/auth layer) -> software-baas-platforms
- PaaS hosting selection (compute layer: Vercel, Fly.io, Railway, Render, Cloudflare Workers, Deno Deploy) -> software-paas-hosting
- SQL tuning and indexing deep dives -> data-sql-optimization
- security reviews and threat modelling -> software-security-appsec
- broader system architecture -> software-architecture-design
What ships with it
25 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 320 B
- assets/csharp/template-csharp-aspnet-efcore.md 27 KB
- assets/go/template-go-chi-sqlc-pgx.md 7.1 KB
- assets/go/template-go-fiber-gorm.md 39 KB
- assets/nodejs/template-nodejs-fastify-drizzle-postgres.md 7.5 KB
- assets/nodejs/template-nodejs-prisma-postgres.md 22 KB
- assets/python/template-python-fastapi-sqlalchemy.md 32 KB
- assets/rust/template-rust-axum-seaorm.md 37 KB
- assets/rust/template-rust-axum-sqlx.md 7.2 KB
- data/sources.json 67 KB
- data/versions.json 2.3 KB
- learnings.consolidated.md 592 B
- learnings.md 384 B
- references/backend-best-practices.md 12 KB
- references/csharp-best-practices.md 45 KB
- references/database-patterns.md 21 KB
- references/edge-deployment-guide.md 7.3 KB
- references/go-best-practices.md 18 KB
- references/infrastructure-economics.md 17 KB
- references/message-queues-background-jobs.md 22 KB
- references/nodejs-best-practices.md 23 KB
- references/operational-playbook.md 33 KB
- references/python-best-practices.md 24 KB
- references/rpc-and-transport-patterns.md 4.6 KB
- references/rust-best-practices.md 18 KB
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.
- 9d ago First seen · 255 lines · 40 tokens per session scan A 7f25addcf9b0
software-backend is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 40 tokens to every session and 3,259 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 2026-09-03.
Other skills, from other repositories
architecture-patterns
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or…
saga-orchestration
Implement saga patterns for distributed transactions and cross-aggregate workflows. Use this skill when implementing distributed transactions across microservices where 2PC is unavailable, designing compensating actions for failed order workflows that span inventory, payment, and shipping services, building…
fastapi-templates
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
api-design-principles
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
error-handling-patterns
Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.