1stANUNNAKI1stANUNNAKI/majlis/skills/google-antigravity-sdk/SKILL.md

google-antigravity-sdk

Skill2 starsChanged 3 months agoMITView on GitHub

Design, implement, and debug autonomous AI agents and multi-agent systems using the Google Antigravity (AGY) SDK. ACTIVATE this skill when the user wants to create, configure, or orchestrate Google Antigravity agents.

Reads credentials

1 other project uses a version of this, 1 of them edited.

Adopted by

Most recently taken up by

google-antigravity/antigravity-sdk-pythonedited, first seen May 13, 2026

Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
google-antigravity/antigravity-sdk-python★ 3.9k56% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository93 other files it gives its agents.
- AGENTS.mdAGENTS.md
- npm/AGENTS.mdAGENTS.md
- advanced-image-slicing-skillSkill
- agents-sdkSkill
- agent-weaver-builderSkill
- alphafold-database-fetch-and-analyzeSkill
- alphagenome-single-variant-analysisSkill
- animation-scroll-effectsSkill
- backend-api-shield-servicesSkill
- chembl-databaseSkill
- chronicle-logger-timestampSkill
- cicd-automation-deploySkill
- cinematic-animator-gsapSkill
- clinical-trials-databaseSkill
- clinvar-databaseSkill
- cloudflare-ai-resourcesSkill
- cloudflare-email-serviceSkill
- cloudflare-one-migrationsSkill
- cloudflare-oneSkill
- cloudflareSkill
- data-modeler-schemaSkill
- dbsnp-databaseSkill
- design-system-master-hslSkill
- durable-objectsSkill
- embl-ebi-olsSkill
- encode-ccres-databaseSkill
- ensembl-databaseSkill
- explode-animation-skillSkill
- find-skillsSkill
- foldseek-structural-searchSkill
- frontend-clean-coder-jsSkill
- gnomad-databaseSkill
- gtex-databaseSkill
- human-protein-atlas-databaseSkill
- inner-learner-feedbackSkill
- integrative-architect-docsSkill
- intent-observer-audit360Skill
- interpro-databaseSkill
- isolated-sandbox-environmentSkill
- jaspar-databaseSkill
- k6-load-testingSkill
- lightweight-dep-managerSkill
- literature-search-arxivSkill
- literature-search-biorxivSkill
- literature-search-europepmcSkill
- literature-search-openalexSkill
- maestro-hadi-orchestrationSkill
- majlis-rulesSkill
- marketing-funnel-skillSkill
- ncbi-sequence-fetchSkill
- neuro-marketing-copywriterSkill
- nuclei-security-auditorSkill
- openfda-databaseSkill
- opentargets-databaseSkill
- owasp-zap-api-shieldSkill
- pdb-databaseSkill
- pdf-scan-layer-cleanerSkill
- premium-visual-polish-skillSkill
- protein-sequence-msaSkill
- protein-sequence-similarity-searchSkill
- The first 60 shown.

The file

Show its rules and text

We split this skill into the rules it gives an agent

27 rules. About 0 are common, 4 are distinctive, and 23 are very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
23
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Distinctive:
Before proceeding with any Google Antigravity tasks, ensure the environment is ready:
line 15
Distinctive:
Verify Applicability: If operating in an existing codebase, verify that using this Python SDK is possible and appropriate for the project.
line 18
Very specific:
Check Dependencies: Check if google-antigravity is listed in the project's dependencies (e.g., requirements.txt, pyproject.toml).
line 20
Very specific:
Install Package: Ensure the google-antigravity Python package is installed.
line 22
Very specific:
Authentication Setup: Check for a valid GEMINI_API_KEY environment variable or a .env file (required to access Gemini models).
line 24
Distinctive:
If credentials are missing, you MUST actively help the user get set up with an API key by providing the following link:
line 26
Very specific:
Default to Google AI Studio: https://aistudio.google.com/app/api-keys
line 28
Distinctive:
Use the following information to dig deeper into specific topics based on the user request.
line 36
Very specific:
If the user needs to understand the high-level overview and core concepts of the Google Antigravity SDK (Agent, Conversation, Connection), …
line 42
Very specific:
If the user needs to perform advanced agent configuration, select appropriate models, or understand the critical rules for model …
line 45
Very specific:
If the user needs to extend an agent's capabilities by integrating Model Context Protocol (MCP) servers, or configure tool permissions for …
line 48
Very specific:
If the user needs to define safety policies, resolve execution order, or restrict agent actions using predicates, read …
line 51
Very specific:
If the user needs to debug failed agents, stream logs, or implement error recovery using hooks to make agents robust, read …
line 54
Very specific:
If the user needs to monitor costs, track token usage (including thinking tokens), or build custom audit logs for advanced monitoring, read …
line 57
Very specific:
If the user needs to see a list of built-in tools and understand their default state, read references/built_in_tools.md.
line 60
Very specific:
If the user needs to implement basic agent behavior, streaming responses, or expose internal thoughts, read …
line 64
Very specific:
If the user needs to equip an agent with custom capabilities (tools) derived from Python functions, or maintain agent state across tool …
line 66
Very specific:
If the user needs to shape an agent's persona, define its system instructions, or dynamically adapt its behavior, read …
line 69
Very specific:
If the user needs to build multimodal agents capable of processing images and PDFs, or generating visual content, read …
line 72
Very specific:
If the user needs to implement multi-agent delegation, allowing a main agent to spawn and orchestrate subagents for complex tasks, read …
line 75
Very specific:
If the user needs to connect an agent to external services via MCP (Stdio or SSE), read examples/getting_started/mcp_tools.md.
line 78
Very specific:
If the user needs to create proactive agents that respond to time-based events or file system triggers in the background, read …
line 80
Very specific:
If the user needs to intercept agent lifecycle events (e.g., pre/post turn, tool execution, errors) to customize execution flow, read …
line 83
Very specific:
If the user needs to implement persistent agents that remember past interactions across sessions, read …
line 86
Very specific:
If the user needs to override the default application data directory for agent artifacts, scratch files, and media storage, read …
line 89
Very specific:
If the user needs an agent to output structured data (e.g., JSON matching a Pydantic schema) for reliable integration, read …
line 92
Very specific:
If the user needs to add, configure, or load agent skills into the Google Antigravity SDK agent, read …
line 95

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

Google Antigravity SDK

Installation & Setup

Before proceeding with any Google Antigravity tasks, ensure the environment is ready:

Verify Applicability: If operating in an existing codebase, verify that using this Python SDK is possible and appropriate for the project.
Check Dependencies: Check if google-antigravity is listed in the project's dependencies (e.g., requirements.txt, pyproject.toml).
Install Package: Ensure the google-antigravity Python package is installed.
Authentication Setup: Check for a valid GEMINI_API_KEY environment variable or a .env file (required to access Gemini models).
- If credentials are missing, you MUST actively help the user get set up with an API key by providing the following link:
  - Default to Google AI Studio: https://aistudio.google.com/app/api-keys
- Explain that the API key can be passed explicitly in code as shorthand (e.g., LocalAgentConfig(api_key="...")) or automatically read from the environment.

Routing Table

Use the following information to dig deeper into specific topics based on the user request. Read the referenced files or explore the directories to find relevant information.

References

If the user needs to understand the high-level overview and core concepts of the Google Antigravity SDK (Agent, Conversation, Connection), read references/architecture.md.
If the user needs to perform advanced agent configuration, select appropriate models, or understand the critical rules for model identifiers to avoid assumptions, read references/agent_configuration.md.
If the user needs to extend an agent's capabilities by integrating Model Context Protocol (MCP) servers, or configure tool permissions for the agent, read references/mcp_integration.md.
If the user needs to define safety policies, resolve execution order, or restrict agent actions using predicates, read references/safety_policies.md.
If the user needs to debug failed agents, stream logs, or implement error recovery using hooks to make agents robust, read references/error_handling.md.
If the user needs to monitor costs, track token usage (including thinking tokens), or build custom audit logs for advanced monitoring, read references/observability.md.
If the user needs to see a list of built-in tools and understand their default state, read references/built_in_tools.md.

Examples

If the user needs to implement basic agent behavior, streaming responses, or expose internal thoughts, read examples/getting_started/hello_world.md.
If the user needs to equip an agent with custom capabilities (tools) derived from Python functions, or maintain agent state across tool execution, read examples/getting_started/custom_tool.md.
If the user needs to shape an agent's persona, define its system instructions, or dynamically adapt its behavior, read examples/getting_started/persona_config.md.
If the user needs to build multimodal agents capable of processing images and PDFs, or generating visual content, read examples/getting_started/multimodal.md.
If the user needs to implement multi-agent delegation, allowing a main agent to spawn and orchestrate subagents for complex tasks, read examples/getting_started/subagents.md.
If the user needs to connect an agent to external services via MCP (Stdio or SSE), read examples/getting_started/mcp_tools.md.
If the user needs to create proactive agents that respond to time-based events or file system triggers in the background, read examples/getting_started/periodic_trigger.md.
If the user needs to intercept agent lifecycle events (e.g., pre/post turn, tool execution, errors) to customize execution flow, read examples/getting_started/hooks.md.
If the user needs to implement persistent agents that remember past interactions across sessions, read examples/getting_started/persistence.md.
If the user needs to override the default application data directory for agent artifacts, scratch files, and media storage, read examples/getting_started/app_data_dir_override.md.
If the user needs an agent to output structured data (e.g., JSON matching a Pydantic schema) for reliable integration, read examples/getting_started/structured_output.md.
If the user needs to add, configure, or load agent skills into the Google Antigravity SDK agent, read examples/getting_started/agent_skills.md.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

It worked
Partly
It didn't

What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free