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 jdrhyne/agent-skills --skill geminigit clone --depth 1 https://github.com/jdrhyne/agent-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/jdrhyne/agent-skills/gemini)<a href="https://agentmods.dev/skills/jdrhyne/agent-skills/gemini"><img src="https://agentmods.dev/badge/skills/jdrhyne/agent-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/skills/jdrhyne/agent-skills/gemini"><img src="https://agentmods.dev/badge/skills/jdrhyne/agent-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 | $0.00053 | $0.02608 |
| Opus 5.5 | $0.00021 | $0.01043 |
| Sonnet 5.5 | $0.00011 | $0.00522 |
| Haiku 4.5 | $0.00005 | $0.00261 |
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 1mo 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
95% identical to gemini — 15 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.
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini Skill Guide
When to Use Gemini
- WHEN ASKED TO BE ACTIVATED
- Code Review: Comprehensive code reviews across multiple files
- Plan Review: Analyzing architectural plans, technical specifications, or project roadmaps
- Big Context Processing: Tasks requiring >200k tokens of context (entire codebases, documentation sets)
- Multi-file Analysis: Understanding relationships and patterns across many files
⚠️ Critical: Background/Non-Interactive Mode Warning
NEVER use --approval-mode default in background or non-interactive shells (like Claude Code tool calls). It will hang indefinitely waiting for approval prompts that cannot be provided.
For automated/background reviews:
- ✅ Use
--approval-mode yolofor fully automated execution - ✅ OR wrap with timeout:
timeout 300 gemini ... - ❌ NEVER use
--approval-mode defaultwithout interactive terminal
Symptoms of hung Gemini:
- Process running 20+ minutes with 0% CPU usage
- No network activity
- Process state shows 'S' (sleeping)
Fix hung process:
# Check if hung
ps aux | grep gemini | grep -v grep
# Kill if necessary
pkill -9 -f "gemini.*gemini-3-pro-preview"
Running a Task
-
Ask the user (via
AskUserQuestion) which model to use in a single prompt. Available models:gemini-3-pro-preview⭐ (flagship model, best for coding & complex reasoning, 35% better at software engineering than 2.5 Pro)gemini-3-flash(sub-second latency, distilled from 3 Pro, best for speed-critical tasks)gemini-2.5-pro(legacy option, strong all-around performance)gemini-2.5-flash(legacy option, cost-efficient with thinking capabilities)gemini-2.5-flash-lite(legacy option, fastest processing)
-
Select the approval mode based on the task:
default: Prompt for approval (⚠️ ONLY for interactive terminal sessions)auto_edit: Auto-approve edit tools only (for code reviews with suggestions)yolo: Auto-approve all tools (✅ REQUIRED for background/automated tasks)
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.
- 1mo ago First seen · 233 lines · 53 tokens per session scan A c701e3c038ff
gemini is a skill published in the GitHub repository jdrhyne/agent-skills (240 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 2,608 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to gemini, differing in 15 lines, and is treated as a copy.
Other skills, from other repositories
agent-code-analyzer
Agent skill for code-analyzer - invoke with $agent-code-analyzer.
pr-review-triage
Watch open PRs, check CI status, review staleness, merge conflicts, and unanswered review comments. Produces a prioritized watchlist.
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.
make-pr-easy-to-review
Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".
thermo-nuclear-code-quality-review
Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
code-quality
Drive static-analysis code quality in pi-agent-dashboard with Biome (analyze → fix → test), in changed-files or whole-repo mode. Use when asked to "improve code quality", "lint and fix", "clean up warnings", "fix Biome issues", "run static analysis", or when setting a code-quality goal. Skip for one-line edits.