Antigravity Skill Vault is a collection of reusable Agent Skills for Google Antigravity, covering software development, operations, security, and business work. It is for people who want Antigravity agents to follow specialized expertise, personas, and structured workflows. The catalogue skills are entries from this collection.
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 rmyndharis/antigravity-skills --skill backend-development-feature-developmentgit clone --depth 1 https://github.com/rmyndharis/antigravity-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/rmyndharis/antigravity-skills/backend-development-feature-development)<a href="https://agentmods.dev/skills/rmyndharis/antigravity-skills/backend-development-feature-development"><img src="https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/backend-development-feature-development/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/rmyndharis/antigravity-skills/backend-development-feature-development"><img src="https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/backend-development-feature-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 32 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00031 | $0.02271 |
| Opus 5.5 | $0.00012 | $0.00908 |
| Sonnet 5.5 | $0.00006 | $0.00454 |
| Haiku 4.5 | $0.00003 | $0.00227 |
Grade A, and why
backend-development-feature-development 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 2mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- backend-development-feature-development — 100% identical, 2 lines differ
- backend-development-feature-development — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrate end-to-end feature development from requirements to production deployment:
[Extended thinking: This workflow orchestrates specialized agents through comprehensive feature development phases - from discovery and planning through implementation, testing, and deployment. Each phase builds on previous outputs, ensuring coherent feature delivery. The workflow supports multiple development methodologies (traditional, TDD/BDD, DDD), feature complexity levels, and modern deployment strategies including feature flags, gradual rollouts, and observability-first development. Agents receive detailed context from previous phases to maintain consistency and quality throughout the development lifecycle.]
Use this skill when
- Coordinating end-to-end feature delivery across backend, frontend, and data
- Managing requirements, architecture, implementation, testing, and rollout
- Planning multi-service changes with deployment and monitoring needs
- Aligning teams on scope, risks, and success metrics
Do not use this skill when
- The task is a small, isolated backend change or bug fix
- You only need a single specialist task, not a full workflow
- There is no deployment or cross-team coordination involved
Instructions
- Confirm feature scope, success metrics, and constraints.
- Select a methodology and define phase outputs.
- Orchestrate implementation, testing, and security validation.
- Prepare rollout, monitoring, and documentation plans.
Safety
- Avoid production changes without approvals and rollback plans.
- Validate data migrations and feature flags in staging first.
Configuration Options
Development Methodology
- traditional: Sequential development with testing after implementation
- tdd: Test-Driven Development with red-green-refactor cycles
- bdd: Behavior-Driven Development with scenario-based testing
- ddd: Domain-Driven Design with bounded contexts and aggregates
Feature Complexity
- simple: Single service, minimal integration (1-2 days)
- medium: Multiple services, moderate integration (3-5 days)
- complex: Cross-domain, extensive integration (1-2 weeks)
- epic: Major architectural changes, multiple teams (2+ weeks)
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.
- 2mo ago First seen · 181 lines · 31 tokens per session scan A 7f42efa046d3
backend-development-feature-development is a skill published in the GitHub repository rmyndharis/antigravity-skills (1,938 stars, last pushed 21d ago), licensed MIT. It adds 31 tokens to every session and 2,271 once invoked, about $0.0001 per session on Opus 5.5. 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 skills, from other repositories
analyzing-api-gateway-access-logs
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
api-security-best-practices
Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities.
api-endpoint-builder
Builds production-ready REST API endpoints with validation, error handling, authentication, and documentation. Follows best practices for security and scalability.
amazon-alexa
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
apify-actorization
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
appdeploy
Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.