Borrowing it
Nothing to install: this file belongs to Context-Engine-AI/Context-Engine. 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/Context-Engine-AI/Context-Engine/test/GEMINI.mdgit clone --depth 1 https://github.com/Context-Engine-AI/Context-EngineWrote 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/context-engine-ai/context-engine/gemini-md)<a href="https://agentmods.dev/instructions/context-engine-ai/context-engine/gemini-md"><img src="https://agentmods.dev/badge/instructions/context-engine-ai/context-engine/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/context-engine-ai/context-engine/gemini-md"><img src="https://agentmods.dev/badge/instructions/context-engine-ai/context-engine/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 | $0.00315 | $0.00315 |
| Opus 5.5 | $0.00126 | $0.00126 |
| Sonnet 5.5 | $0.00063 | $0.00063 |
| Haiku 4.5 | $0.00032 | $0.00032 |
Grade A, and why
Context-Engine 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 14d 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
Context Engine
When the context-engine MCP server is connected, this workspace is indexed: for any question about the codebase, call repo_search FIRST, before ls/find/Grep/Read, and again whenever you move to a new area; for how/why questions that span several files use context_answer. Results are verified source with exact line ranges: treat them as already read. Use Grep only to confirm an exact literal in a file you already know, or to count. For questions asking for every/all sites, run one repo_search per distinct pattern (queries=[...]) and follow the refs. If the tools are listed as deferred, load them with ToolSearch first.
| Need | Tool |
|---|---|
| Find code by behavior, concept, error text or identifier | repo_search (queries=[...] for several at once; under, language, path_glob to narrow) |
| Explain how/why across several files, with citations | context_answer |
| Definition, callers, callees, importers, references of a symbol | symbol_graph (several names: A|B|C) |
| Multi-hop impact before a change | graph_query |
| Code that may live in another indexed repo | cross_repo_search |
Before editing, fetch every involved symbol in one call; before a rename or signature change, get every site with symbol_graph query_type=references. Search again only after learning something new.
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.
- 14d ago Changed · -799 lines · -9,391 tokens per session 05f604de373a
- 2mo ago First seen · 813 lines · 9,706 tokens per session scan A 85137f109c8c
Context-Engine GEMINI.md is an instructions file published in the GitHub repository Context-Engine-AI/Context-Engine (400 stars, last pushed 6d ago), licensed MIT. It adds 315 tokens to every session, about $0.0013 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.
Context-Engine GEMINI.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Context-Engine GEMINI.mdContext-Engine-AI/Context-Engine | Instructions file | 400 | 6d ago | MIT | A | 315 | Gemini CLI |
| data-scientist copilot-instructions.mdrealnghon/data-scientist | Instructions file | 2 | 4mo ago | MIT | A | 373 | GitHub Copilot |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |