gemini

Gemini CLI Runner

Invokes Google's Gemini CLI in non-interactive mode to get an independent response from a non-Claude model. The skill shells out via the Bash tool, captures stdout, and returns the response cleanly.

When to use

• The user explicitly asks to consult Gemini ("ask Gemini", "what does Gemini think", "second opinion from Gemini")
• A crossfire-style multi-model review needs an independent Google-side perspective
• The user wants an external check on a design, code change, or argument and Gemini is the chosen reviewer

Do NOT trigger when:

• The user is asking about Gemini CLI itself (use docs, not this skill)
• The task can be answered from your own knowledge — don't pay the latency for nothing
• Gemini CLI isn't installed (see "Setup check" below)

Setup the user needs

Before this skill works, the user must have:

1. Gemini CLI installed and on PATH. Install with npm install -g @google/gemini-cli (Node 20+).
2. Auth configured — pick one:
   • API key (headless-friendly): GEMINI_API_KEY env var, obtained from https://aistudio.google.com/app/apikey. This is the path of least friction for shell-out.
   • OAuth ("Sign in with Google"): First run gemini interactively, complete the browser flow, then cached credentials live in ~/.gemini/. Free-tier OAuth has stricter quotas than API key.
   • Workspace / Vertex: Set GOOGLE_APPLICATION_CREDENTIALS + GOOGLE_CLOUD_PROJECT (+ GOOGLE_CLOUD_LOCATION for Vertex).

If none is set, gemini -p will either drop into an OAuth flow (which won't work in non-interactive context) or error. Detect and tell the user.

How to invoke

Step 1 — Check that Gemini is available

command -v gemini && gemini --version

If unavailable, tell the user:

Gemini CLI doesn't appear to be installed or on PATH. Install with npm install -g @google/gemini-cli (Node 20+ required), then either set GEMINI_API_KEY or run gemini once interactively to complete OAuth, then retry.

Stop. Do not attempt the call.

Step 2 — Construct the prompt

Same as the Codex skill — assemble the prompt from the user's request, file contents, or a parent-flow-supplied template. For long prompts, use a file rather than inline shell-arg quoting.

Step 3 — Run Gemini from the project directory

gemini -p "$PROMPT" --output-format text -m flash 2>/dev/null

Run from the project's working directory so Gemini can read files referenced in the prompt. Crossfire reviewers read the project's docs and code via the CLI's filesystem tools — they don't just respond to inlined text.

Flag rationale:

• -p — mandatory for non-interactive use. Without it, Gemini drops into the REPL when stdin is a TTY.
• --output-format text — plain text on stdout. Use --output-format json for {response, stats, error} if the parent flow needs structured output.
• -m flash — pick the fast/cheap model. For higher-quality reviews use -m pro (or whatever the current top-tier model is). Defer to user preference if specified.
• 2>/dev/null — suppresses Gemini's progress/spinner output.

Note: Gemini auto-loads GEMINI.md from the cwd as additional context, similar to Claude's CLAUDE.md. For crossfire this is fine — it's project-scoped context the reviewer should see. If you specifically need a clean run with no project context, run from a temp directory (but you'll lose file-access to the very docs the prompt references — almost never what you want for crossfire).

For long prompts:

gemini -p "$(cat /path/to/prompt.md)" --output-format text -m flash 2>/dev/null

Or pipe stdin:

cat /path/to/prompt.md | gemini -p "Review the following:" --output-format text -m flash 2>/dev/null

Step 4 — Capture and return

Capture stdout. Present back with framing:

Gemini says:

Optional flags worth knowing

• --approval-mode yolo (or --yolo) — auto-approves any tool calls Gemini wants to make. Only relevant if the prompt encourages tool use; for pure text-in/text-out reviews, prompt phrasing keeps things clean and you don't need this.
• -m <model> — pin a specific model when the user requests one.
• --output-format stream-json — for streaming JSON events. Use only if the parent flow consumes streamed structured output.

Context-leak gotchas

Gemini auto-loads two things from the working directory that can contaminate output:

1. GEMINI.md — analogous to CLAUDE.md. If the cwd has one, it gets loaded as context. For deterministic crossfire, run from a clean directory or a temp dir.
2. .gemini/.env — environment overrides. Loaded from cwd up the directory tree, then ~/.gemini/.env. Variables can leak from project-specific configs.

If you want a guaranteed-clean Gemini call:

TEMP_DIR=$(mktemp -d)
cd "$TEMP_DIR"
gemini -p "$PROMPT" --output-format text -m flash 2>/dev/null
cd - >/dev/null
rm -rf "$TEMP_DIR"

Error handling

Symptom	Likely cause	Action
command not found	Gemini CLI not installed	Install per Setup section
Hangs / browser opens	OAuth flow triggered in non-interactive context	Set GEMINI_API_KEY instead of relying on OAuth
Exit code 42	Input error (malformed prompt, empty stdin where one was expected)	Check prompt construction
Exit code 53	Turn limit reached	Shouldn't happen on single-turn -p calls; if it does, the prompt may have triggered tool-use loops
Quota exceeded	Free-tier OAuth quota hit	Switch to GEMINI_API_KEY (paid tier) or wait for reset

Windows / Cowork sandbox note

Same caveat as the Codex skill: the user's Gemini CLI is likely installed on Windows; Cowork's Bash runs in a Linux sandbox. If the sandbox can't reach the host binary, install Gemini CLI inside the sandbox (npm install -g @google/gemini-cli) and pass GEMINI_API_KEY as an env var so auth survives the ephemeral sandbox.