Borrowing it
Nothing to install: this file belongs to gondola-ai/gondola-mcp. 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/gondola-ai/gondola-mcp/main/GEMINI.mdgit clone --depth 1 https://github.com/gondola-ai/gondola-mcpWrote 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/instructions/gondola-ai/gondola-mcp/gemini-md)<a href="https://agentmods.dev/instructions/gondola-ai/gondola-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/gondola-ai/gondola-mcp/gemini-md/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/instructions/gondola-ai/gondola-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/gondola-ai/gondola-mcp/gemini-md.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 | $0.00366 | $0.00366 |
| Opus 5.5 | $0.00146 | $0.00146 |
| Sonnet 5.5 | $0.00073 | $0.00073 |
| Haiku 4.5 | $0.00037 | $0.00037 |
Grade A, and why
gondola-mcp GEMINI.md 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 17d 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
Gondola travel tools
Gondola returns hotels with both cash and loyalty-points pricing plus a cents-per-point (CPP) value, so you can recommend the best-value way to pay. Flights and rental cars are cash-priced only: never state or imply an award/points cost for a flight.
Presenting results
- When showing more than one option side by side (hotels, rooms/rates, loyalty accounts, trips, or a rate comparison), a table with a header row reads better than a list.
- Keep columns tight and lead with the value signal (CPP or deal score). Call out the single best-value pick in prose rather than restating every cell.
Using the traveler's context
get_traveler_contextreturns loyalty programs and elite tiers, home airport, preferred airlines and chains, and stated or learned preferences. It is the best source of who this traveler is, so it is worth reading before recommending hotels, flights, or cars.- Elite status changes the real cost of a stay: benefits (late checkout, breakfast, 5th-night-free) and points balances belong in the recommendation alongside the raw price.
update_traveler_profilesaves a preference the traveler shares so later sessions can use it. Tell them when you save one; they can review, edit, or clear saved preferences at https://www.gondola.ai/concierge (Traveler Profile panel).- Use
get_loyalty_accountsfor a detailed points-balance breakdown.
Auth
Every tool uses the traveler's Gondola account through MCP OAuth 2.1. Gemini CLI prompts for the sign-in when it connects; a Gondola account is free and there is no API key.
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.
- 17d ago Changed · +4 lines · +82 tokens per session 3c223af6460c
- 2mo ago First seen · 26 lines · 284 tokens per session scan A e15bd1aac018
gondola-mcp GEMINI.md is an instructions file published in the GitHub repository gondola-ai/gondola-mcp (9 stars, last pushed 17d ago), licensed MIT. It adds 366 tokens to every session, about $0.0015 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 2026-08-31.
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