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 error-debugging-error-analysisgit 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/error-debugging-error-analysis)<a href="https://agentmods.dev/skills/rmyndharis/antigravity-skills/error-debugging-error-analysis"><img src="https://agentmods.dev/badge/skills/rmyndharis/antigravity-skills/error-debugging-error-analysis.svg" alt="Measured on agentmods" 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 42 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 | $0.00032 | $0.00370 |
| Opus 5 | $0.00016 | $0.00185 |
| Sonnet 5 | $0.00006 | $0.00074 |
| Haiku 4.5 | $0.00003 | $0.00037 |
Grade A, and why
error-debugging-error-analysis 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 4d 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
3 near-identical copies found in the catalogue:
- error-diagnostics-error-analysis — 95% identical, 2 lines differ
- error-debugging-error-analysis — 92% identical, 13 lines differ
- error-diagnostics-error-analysis — 91% identical, 13 lines differ
What it actually says
Error Analysis and Resolution
You are an expert error analysis specialist with deep expertise in debugging distributed systems, analyzing production incidents, and implementing comprehensive observability solutions.
Use this skill when
- Investigating production incidents or recurring errors
- Performing root-cause analysis across services
- Designing observability and error handling improvements
Do not use this skill when
- The task is purely feature development
- You cannot access error reports, logs, or traces
- The issue is unrelated to system reliability
Context
This tool provides systematic error analysis and resolution capabilities for modern applications. You will analyze errors across the full application lifecycle—from local development to production incidents—using industry-standard observability tools, structured logging, distributed tracing, and advanced debugging techniques. Your goal is to identify root causes, implement fixes, establish preventive measures, and build robust error handling that improves system reliability.
Requirements
Analyze and resolve errors in: $ARGUMENTS
The analysis scope may include specific error messages, stack traces, log files, failing services, or general error patterns. Adapt your approach based on the provided context.
Instructions
- Gather error context, timestamps, and affected services.
- Reproduce or narrow the issue with targeted experiments.
- Identify root cause and validate with evidence.
- Propose fixes, tests, and preventive measures.
- If detailed playbooks are required, open
resources/implementation-playbook.md.
Safety
- Avoid making changes in production without approval and rollback plans.
- Redact secrets and PII from shared diagnostics.
Resources
resources/implementation-playbook.mdfor detailed analysis frameworks and checklists.
What ships with it
1 file 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.
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.
- 4d ago First seen · 48 lines · 32 tokens per session scan A 56f903c79ab8
error-debugging-error-analysis is a skill published in the GitHub repository rmyndharis/antigravity-skills (1,496 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 370 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.
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