Borrowing it
Nothing to install: this file belongs to davidbuenov/dbv-pdf2md. 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/davidbuenov/dbv-pdf2md/master/GEMINI.mdgit clone --depth 1 https://github.com/davidbuenov/dbv-pdf2mdWrote 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/davidbuenov/dbv-pdf2md/gemini-md)<a href="https://agentmods.dev/instructions/davidbuenov/dbv-pdf2md/gemini-md"><img src="https://agentmods.dev/badge/instructions/davidbuenov/dbv-pdf2md/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 | $0.00608 | $0.00608 |
| Opus 5 | $0.00304 | $0.00304 |
| Sonnet 5 | $0.00122 | $0.00122 |
| Haiku 4.5 | $0.00061 | $0.00061 |
Grade A, and why
dbv-pdf2md 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Instructions for Gemini CLI & Antigravity
This project follows Spec-Driven Development (SDD). Read these files at the start of each session before proposing any code or plan:
| File | Purpose |
|---|---|
dbv-specs-ops/project.config.md |
Project identity: name, author, license and file header template |
dbv-specs-ops/docs/MASTER_PROMPT.md |
Mandatory workflow, rules and boundaries |
dbv-specs-ops/docs/SPECIFICATIONS.md |
Current project requirements |
dbv-specs-ops/docs/ARCHITECTURE.md |
Stack and technical decisions |
dbv-specs-ops/docs/DESIGN.md |
Visual design system: color tokens, typography, components and philosophy (if it exists) |
dbv-specs-ops/memory.md |
Context and Decisions: Qualitative knowledge (ADRs, lessons learned, active context) |
dbv-specs-ops/task.md |
Current state + Context Snapshot |
Note: This file is auto-loaded by both Gemini CLI (
geminiin terminal) and Antigravity (VS Code · Google DeepMind). For Antigravity-specific setup instructions (Planning Mode, Knowledge Items), seedbv-specs-ops/ANTIGRAVITY.md.
⚠️ Core Rules (Strong Pointer)
Read dbv-specs-ops/docs/MASTER_PROMPT.md and follow its workflow strictly. If you detect contradictions between the prompt and project specs, halt and report before proceeding.
All initialization logic (Bootstrap), state checking (Specs Check), lifecycle (Workflow) and coding standards are centrally defined there to avoid cognitive redundancy.
Antigravity-Specific Behavior
(Only applies when running in Antigravity / VS Code · Google DeepMind)
- Planning Mode: When creating a plan, activate Antigravity's native Planning Mode. Create the artifacts (
implementation_plan.md,task.md,walkthrough.md) inside the project workspace root — not only in the conversation brain directory — so they are versioned with the project and accessible to the team and other AI platforms. - Knowledge Items (KIs): After completing a significant milestone, offer to create a Knowledge Item summarizing the project context. This enables seamless context recovery in future sessions without rereading all docs.
- Context Snapshot: At the end of each session or before a conversation limit, write a Context Snapshot to
dbv-specs-ops/task.mdwith the exact next step so work can be resumed instantly.
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.
- 7d ago First seen · 33 lines · 608 tokens per session scan A 912192189a19
dbv-pdf2md GEMINI.md is an instructions file published in the GitHub repository davidbuenov/dbv-pdf2md (0 stars, last pushed 1mo ago), licensed MIT. It adds 608 tokens to every session, about $0.0030 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 2026-08-31.
Other instructions, from other repositories
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