Gemini CLI is a terminal-based AI agent that lets developers interact with Google Gemini models and use tools for tasks such as file operations, shell commands, web fetching, and search. Developers use it from the command line, and the catalogue add-ons extend its workflows and integrations.
Borrowing it
Nothing to install: this file belongs to google-gemini/gemini-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/google-gemini/gemini-cli/main/.gemini/skills/behavioral-evals/SKILL.mdgit clone --depth 1 https://github.com/google-gemini/gemini-cliWrote 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/google-gemini/gemini-cli/behavioral-evals)<a href="https://agentmods.dev/skills/google-gemini/gemini-cli/behavioral-evals"><img src="https://agentmods.dev/badge/skills/google-gemini/gemini-cli/behavioral-evals/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/google-gemini/gemini-cli/behavioral-evals"><img src="https://agentmods.dev/badge/skills/google-gemini/gemini-cli/behavioral-evals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00039 | $0.00616 |
| Opus 5.5 | $0.00016 | $0.00246 |
| Sonnet 5.5 | $0.00008 | $0.00123 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
behavioral-evals 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- behavioral-evals — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Evals
Overview
Behavioral evaluations (evals) are tests that validate the agent's decision-making (e.g., tool choice) rather than pure functionality. They are critical for verifying prompt changes, debugging steerability, and preventing regressions.
[!NOTE] Single Source of Truth: For core concepts, policies, running tests, and general best practices, always refer to evals/README.md.
🔄 Workflow Decision Tree
- Does a prompt/tool change need validation?
- No -> Normal integration tests.
- Yes -> Continue below.
- Is it UI/Interaction heavy?
- Yes -> Use
appEvalTest(AppRig). See creating.md. - No -> Use
evalTest(TestRig). See creating.md.
- Yes -> Use
- Is it a new test?
- Yes -> Set policy to
USUALLY_PASSES. - No ->
ALWAYS_PASSES(locks in regression).
- Yes -> Set policy to
- Are you fixing a failure or promoting a test?
- Fixing -> See fixing.md.
- Promoting -> See promoting.md.
📋 Quick Checklist
1. Setup Workspace
Seed the workspace with necessary files using the files object to simulate a realistic scenario (e.g., NodeJS project with package.json).
- Details in creating.md
2. Write Assertions
Audit agent decisions using rig.setBreakpoint() (AppRig only) or index verification on rig.readToolLogs().
- Details in creating.md
3. Verify
Run single tests locally with Vitest. Confirm stability locally before relying on CI workflows.
- See evals/README.md for running commands.
📦 Bundled Resources
Detailed procedural guides:
- creating.md: Assertion strategies, Rig selection, Mock MCPs.
- fixing.md: Step-by-step automated investigation, architecture diagnosis guidelines.
- promoting.md: Candidate identification criteria and threshold guidelines.
What ships with it
6 files 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 · 57 lines · 39 tokens per session scan A c1ab849bb3b1
behavioral-evals is a skill published in the GitHub repository google-gemini/gemini-cli (107,525 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 616 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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