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.
git clone --depth 1 https://github.com/sparklingneuronics/sparkling-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/commands/sparklingneuronics/sparkling-skills/gemini)<a href="https://agentmods.dev/commands/sparklingneuronics/sparkling-skills/gemini"><img src="https://agentmods.dev/badge/commands/sparklingneuronics/sparkling-skills/gemini/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/commands/sparklingneuronics/sparkling-skills/gemini"><img src="https://agentmods.dev/badge/commands/sparklingneuronics/sparkling-skills/gemini.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 | $0.00023 | $0.00212 |
| Opus 5 | $0.00012 | $0.00106 |
| Sonnet 5 | $0.00005 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
gemini 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 11d 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.
What it actually says
The user wants this delegated to Gemini — run it through Antigravity's agy CLI with a Gemini model (gemini-cli's individual tier is retired; agy is the working successor). Do not answer it yourself. Invoke the agy skill and follow its workflow, using --model "Gemini 3.1 Pro (High)" (or "Gemini 3.5 Flash (High)" for a quick check). Remember agy acts by default (constrain via the prompt for analysis-only intent), allow a generous timeout (cold start can be ~2–3 min), and keep a topic-aware conversation so "continue with gemini" resumes the right thread. If the request below is empty, delegate what the user is currently working on.
Request: $ARGUMENTS
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.
- 11d ago First seen · 8 lines · 23 tokens per session scan A 9272705bc3bf
gemini is a command published in the GitHub repository sparklingneuronics/sparkling-skills (6 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 212 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 2026-08-31.
Other commands, from other repositories
review
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ship
Branch, commit, open PR, gather Claude + every enabled AI reviewer (Copilot, CodeRabbit, etc.), fix/justify/resolve every finding, loop until clean, then merge. Run only when implementation is finished AND the owner has said to ship (e.g. "ship it") — never self-invoke just because the work looks done. To design and…
review
Multi-agent code review with parallel validation.
code-review-teach
Educational code review that teaches while reviewing. Provides constructive feedback, explains best practices, discusses trade-offs, and helps developers improve their coding skills.
hidden-dependencies
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dead-code-clean
Actively find and remove dead code, unused imports, duplicates, and zombie code.