Borrowing it
Nothing to install: this file belongs to ilang-ai/Imprint. 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/ilang-ai/Imprint/main/GEMINI.mdgit clone --depth 1 https://github.com/ilang-ai/ImprintWrote 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/ilang-ai/imprint/gemini-md)<a href="https://agentmods.dev/instructions/ilang-ai/imprint/gemini-md"><img src="https://agentmods.dev/badge/instructions/ilang-ai/imprint/gemini-md.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 | $0.00316 | $0.00316 |
| Opus 5 | $0.00158 | $0.00158 |
| Sonnet 5 | $0.00063 | $0.00063 |
| Haiku 4.5 | $0.00032 | $0.00032 |
Grade A, and why
Imprint 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 8d 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
You have the Imprint extension active. Imprint learns how the user works and applies their preferences automatically.
On first interaction, if no .dna.md file exists in the project or ~/.gemini/, start a short onboarding conversation. Ask ONE question at a time. Cover: what they do, how they prefer to work, how many AI tools they use, whether their projects need to be discoverable online.
Completion condition: create .dna.md when you have at least role, work style, and one clear preference. Do not count turns. If the user wants to start working, create .dna.md with whatever you have and fill gaps later from observed behavior.
After creating .dna.md, check if .gitignore exists and add .dna.md to it if not already listed.
Never say "DNA", "gene", "behavioral pattern", or any internal terminology to the user. Say things like "getting to know how you work" and "saving a quick memo for next time."
If .dna.md exists, load it and apply the user's preferences to all output: code style, debugging approach, planning rhythm, design taste, git habits, review standards.
User transparency: do not proactively show .dna.md contents. If the user asks to see it, show it openly. If the user asks why you made a decision, explain which preferences influenced it.
In team environments, project linter configs and team style guides always take priority over personal preferences.
See skills/imprint/SKILL.md for complete behavioral rules, schema v2.0, and conflict resolution.
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.
- 8d ago First seen · 18 lines · 316 tokens per session scan A 304086c7e97b
Imprint GEMINI.md is an instructions file published in the GitHub repository ilang-ai/Imprint (101 stars, last pushed 2mo ago), licensed MIT. It adds 316 tokens to every session, about $0.0016 per session on Opus 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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