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 Bilal140202/the-lord-of-the-skills --skill ssstainlesss__antigravity-launchpadgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote 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/bilal140202/the-lord-of-the-skills/ssstainlesss__antigravity-launchpad)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/ssstainlesss__antigravity-launchpad"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/ssstainlesss__antigravity-launchpad/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/bilal140202/the-lord-of-the-skills/ssstainlesss__antigravity-launchpad"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/ssstainlesss__antigravity-launchpad.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00025 | $0.00834 |
| Opus 5 | $0.00013 | $0.00417 |
| Sonnet 5 | $0.00005 | $0.00167 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
backend-agent 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 8d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Backend Agent - API & Server Specialist
When to use
- Building REST APIs or GraphQL endpoints
- Database design and migrations
- Authentication and authorization
- Server-side business logic
- Background jobs and queues
When NOT to use
- Frontend UI -> use Frontend Agent
- Mobile-specific code -> use Mobile Agent
Core Rules
- DRY (Don't Repeat Yourself): Business logic in
Service, data access logic inRepository - SOLID:
- Single Responsibility: Classes and functions should have one responsibility
- Dependency Inversion: Use FastAPI's
Dependsfor dependency injection
- KISS: Keep it simple and clear
Architecture Pattern
Router (HTTP) → Service (Business Logic) → Repository (Data Access) → Models
Repository Layer
- File:
src/[domain]/repository.py - Role: Encapsulate DB CRUD and query logic
- Principle: No business logic, return SQLAlchemy models
Service Layer
- File:
src/[domain]/service.py - Role: Business logic, Repository composition, external API calls
- Principle: Business decisions only here
Router Layer
- File:
src/[domain]/router.py - Role: Receive HTTP requests, input validation, call Service, return response
- Principle: No business logic, inject Service via DI
Core Rules
- Clean architecture: router → service → repository → models
- No business logic in route handlers
- All inputs validated with Pydantic
- Parameterized queries only (never string interpolation)
- JWT + bcrypt for auth; rate limit auth endpoints
- Async/await consistently; type hints on all signatures
- Custom exceptions via
src/lib/exceptions.py(not raw HTTPException)
Dependency Injection
# src/recipes/routers/dependencies.py
async def get_recipe_service(db: AsyncSession = Depends(get_db)) -> RecipeService:
repository = RecipeRepository(db)
return RecipeService(repository)
# src/recipes/routers/base_router.py
@router.get("/{recipe_id}")
async def get_recipe(
recipe_id: str,
service: RecipeService = Depends(get_recipe_service)
):
return await service.get_recipe(recipe_id)
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.
- 8d ago First seen · 108 lines · 25 tokens per session scan A e00ab0f4dfa8
backend-agent is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 25 tokens to every session and 834 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 2026-09-03.
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