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 agentmods add skills/aleksbuss/orchestra/gemininpx skills add aleksbuss/orchestra --skill geminigit clone --depth 1 https://github.com/aleksbuss/orchestraWrote 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/aleksbuss/orchestra/gemini)<a href="https://agentmods.dev/skills/aleksbuss/orchestra/gemini"><img src="https://agentmods.dev/badge/skills/aleksbuss/orchestra/gemini.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.00234 |
| Opus 5 | $0.00009 | $0.00117 |
| Sonnet 5 | $0.00003 | $0.00047 |
| Haiku 4.5 | $0.00002 | $0.00023 |
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 5d 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.
This is a copy
83% identical to gemini — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Gemini CLI
Use Gemini in one-shot mode with a positional prompt (avoid interactive mode).
Quick start
gemini "Answer this question..."gemini --model <name> "Prompt..."gemini --output-format json "Return JSON"
Extensions
- List:
gemini --list-extensions - Manage:
gemini extensions <command>
Notes
- If auth is required, run
geminionce interactively and follow the login flow. - Avoid
--yolofor safety.
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.
- 5d ago First seen · 44 lines · 17 tokens per session scan A 39632404828b
gemini is a skill published in the GitHub repository aleksbuss/orchestra (2 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 234 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to gemini, differing in 17 lines, and is treated as a copy.
Other skills, from other repositories
data-agent-skill
Data processing and analysis specialist for the OpenClaw multi-agent system. Use this skill when the task involves: parsing CSV/JSON/Excel files, data cleaning and transformation, SQL queries, statistical analysis, generating charts or visualizations, aggregating data from multiple sources, or extracting insights from…
weights-and-biases
W&B: log ML experiments, sweeps, model registry, dashboards.
nemo-curator
Curate LLM training data: dedupe, filter, PII redaction.
ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
open-source
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browseruse, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle…
darwinian-evolver
Evolve prompts/regex/SQL/code with Imbue's evolution loop.