Context-Engineering GEMINI.md

Context-Engineering GEMINI.md is an instructions file for Gemini CLI from jasontang-ai/Context-Engineering. It costs 4,417 tokens per session, scanned A, original, MIT.

A set of instructions for Gemini CLI that organizes how it reasons through problems, analyzes code, generates code, and researches technical topics.

In plain words
What is it for?
Use it for systematic problem solving, code analysis and generation, and technical research in Gemini CLI.
Why use it?
It gives the agent a repeatable way to break down complex work, check its results, and improve its solution.

Instructions file for Gemini CLI

About the project

Context Engineering is a handbook and research-oriented course about designing the information supplied to language models at inference time, including context selection, organization, orchestration, and optimization. It is for people building or studying AI agents and other systems that need to provide models with the right information for each task. The catalogue entries contain commands and instructions for using these ideas with coding-agent tools.

jasontang-ai/Context-Engineering · 9,238 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/jasontang-ai/context-engineering/gemini-md
Clone the repo
git clone --depth 1 https://github.com/jasontang-ai/Context-Engineering

Made for: Gemini CLI.

Wrote 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.

agentmods badge for Context-Engineering GEMINI.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/jasontang-ai/context-engineering/gemini-md.svg)](https://agentmods.dev/instructions/jasontang-ai/context-engineering/gemini-md)
Your own site
<a href="https://agentmods.dev/instructions/jasontang-ai/context-engineering/gemini-md"><img src="https://agentmods.dev/badge/instructions/jasontang-ai/context-engineering/gemini-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 4,417 This file is loaded in full into every session.
When invoked 4,417 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.04417 $0.04417
Opus 5 $0.02209 $0.02209
Sonnet 5 $0.00883 $0.00883
Haiku 4.5 $0.00442 $0.00442

Measured 5d ago against content hash 6768e17364cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Context-Engineering 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 5d 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.

GEMINI.md · 749 lines

How it starts

The opening of the file, as written. The whole thing — 749 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEMINI.md - Cognitive Operating System

This document defines enhanced reasoning patterns, protocol shells, and cognitive frameworks to be used by Gemini CLI. These tools provide structured thinking, step-by-step reasoning, and recursive self-improvement capabilities.

Core Reasoning Frameworks

Systematic Problem Solving

/reasoning.systematic{
    intent="Break down complex problems into manageable steps with clear logic",
    input={
        problem="<problem_statement>",
        constraints="<any_constraints>",
        context="<relevant_context>"
    },
    process=[
        /understand{action="Restate the problem and identify the goal"},
        /analyze{action="Break down the problem into components"},
        /plan{action="Create a step-by-step approach"},
        /execute{action="Work through each step methodically"},
        /verify{action="Check the solution against the original problem"},
        /refine{action="Improve the solution if needed"}
    ],
    output={
        understanding="Clear restatement of the problem",
        approach="Structured step-by-step plan",
        solution="Detailed implementation",
        verification="Proof of correctness"
    }
}

Code Analysis & Generation

/code.analyze{
    intent="Deeply understand code structure, patterns, and potential improvements",
    input={
        code="<code_to_analyze>",
        language="<programming_language>",
        focus="<specific_aspect_to_focus_on>"
    },
    process=[
        /parse{action="Identify key components and their relationships"},
        /evaluate{
            structure="Assess organization and architecture",
            quality="Identify strengths and weaknesses",
            patterns="Recognize design patterns in use"
        },
        /trace{action="Follow execution paths and data flow"},
        /suggest{
            improvements="Identify potential optimizations",
            alternatives="Suggest alternative approaches"
        }
    ],
    output={
        summary="High-level overview of the code",
        components="Breakdown of key elements",
        quality_assessment="Evaluation of code quality",
        recommendations="Suggested improvements"
    }
}

Read the full file on GitHub · 749 lines

Changes

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.

  1. 5d ago First seen · 749 lines · 4,417 tokens per session scan A 6768e17364cb

Subscribe to this mod's changes

Context-Engineering GEMINI.md is an instructions file published in the GitHub repository jasontang-ai/Context-Engineering (9,238 stars, last pushed 6mo ago), licensed MIT. It adds 4,417 tokens to every session, about $0.0221 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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