# Technical Document Extraction: LLM Agent Prompt and Trajectory Structure This image is a technical diagram illustrating the structured components of a Large Language Model (LLM) prompt and the subsequent iterative trajectory for solving a software engineering task. ## 1. Component Isolation The diagram is organized vertically into three primary segments: * **Header (Prompt Configuration):** Three large, black-bordered blocks defining the initial context. * **Main Trajectory (Iterative Loop):** A series of alternating blue and orange bars representing the interaction between the agent and the environment. * **Footer (Output):** A final yellow block representing the resulting artifact. --- ## 2. Detailed Content Transcription ### Region 1: Prompt Configuration (Header) These blocks establish the "System" and "User" context before the agent begins work. | Block Title | Content / Bullet Points | | :--- | :--- | | **System Prompt** | • Describe environment and commands<br>• Specify response format | | **Demonstration** | Full trajectory of a successful example | | **Issue statement** | • Give reported issue description<br>• Instructions to resolve issue<br>• High-level strategy tips | ### Region 2: Iterative Trajectory (Main Chart) This section depicts a ReAct-style (Reasoning and Acting) loop. The colors indicate the source of the information. * **Blue Outlined Bars (Agent Output):** Labeled **"Thought & Action"**. These represent the model's internal reasoning and the command it chooses to execute. * **Orange Outlined Bars (Environment Output):** Labeled **"Environment Response"**. * The first two orange bars feature a diagonal grey-striped pattern and are labeled **"(collapsed)"**, indicating historical context that may be truncated or summarized. * A vertical ellipsis (**⋮**) indicates that this loop repeats multiple times. * The final orange bar is solid, labeled **"Environment Response"**, representing the most recent feedback. * **Final Blue Bar:** Labeled **"Submit"**, indicating the agent has completed the task. ### Region 3: Resulting Artifact (Footer) A yellow-shaded block representing the final output of the process. | Label | Text Content (Code/Diff) | | :--- | :--- | | **Patch File** | `diff --git a/src/sqlfluff/rules/L060.py` <br> `b/src/sqlfluff/rules/L060.py` <br> `--- a/src/sqlfluff/rules/L060.py` <br> `+++ b/src/sqlfluff/rules/L060.py` | --- ## 3. Flow and Logic Analysis 1. **Initialization:** The process begins with a comprehensive **System Prompt**, a **Demonstration** (few-shot learning), and the specific **Issue statement**. 2. **The Loop:** The agent enters a cycle of **Thought & Action** (Blue) followed by an **Environment Response** (Orange). * *Trend:* The diagram shows that earlier responses are "collapsed" to manage context window limits, while the most recent response remains fully visible. 3. **Termination:** Once the agent determines the issue is resolved, it issues a **Submit** command. 4. **Output:** The final result is a **Patch File**, specifically shown as a git diff targeting a Python file in the `sqlfluff` library (`L060.py`). ## 4. Technical Metadata * **Language:** English (100%). * **Visual Coding:** * **Black Borders:** Static prompt instructions. * **Blue Borders:** Agent-generated content. * **Orange Borders:** System/Environment-generated feedback. * **Yellow Background:** Final data product/artifact.

## Technical Document Layout: Debugging Workflow Interface ### Overview The image depicts a structured technical document interface designed for debugging workflows. It combines textual instructions, color-coded components, and a code patch visualization. The layout emphasizes step-by-step problem resolution through a combination of natural language prompts, environmental interactions, and code modifications. ### Components/Axes 1. **Header Sections** (Top 1/3 of image): - **System Prompt** (Blue background): - Text: "Describe environment and commands • Specify response format" - **Demonstration** (Blue background): - Text: "Full trajectory of a successful example" - **Issue Statement** (Blue background): - Text: "Give reported issue description • Instructions to resolve issue • High-level strategy tips" 2. **Main Workflow** (Middle 2/3 of image): - **Thought & Action** (Blue box with white text): - Repeated 3x with alternating blue/red color coding - **Environment Response** (Red box with gray text): - Labeled "collapsed" in parentheses - Appears 3x with alternating blue/red color coding - **Submit** (Blue box with black text): - Contains code patch details 3. **Legend** (Bottom of image): - Color key: - Blue: Thought & Action - Red: Environment Response - Yellow: Patch File 4. **Code Patch** (Bottom section): - Yellow background with code diff: ``` diff --git a/src/sqlfluff/rules/L060.py b/src/sqlfluff/rules/L060.py --- a/src/sqlfluff/rules/L060.py +++ b/src/sqlfluff/rules/L060.py ``` ### Detailed Analysis 1. **System Prompt Section**: - Contains two bullet points specifying requirements for environment description and response formatting - Positioned at top-left, establishing foundational guidelines 2. **Demonstration Section**: - Single-line instruction emphasizing example-based learning - Positioned centrally, acting as transitional element 3. **Issue Statement Section**: - Three bullet points outlining required components for issue reporting - Positioned top-right, providing resolution framework 4. **Workflow Components**: - **Thought & Action** (Blue): - Contains reasoning steps (text not visible in image) - Alternates with Environment Response in iterative pattern - **Environment Response** (Red): - Contains system feedback (text not visible in image) - Marked as "collapsed" suggesting expandable/collapsible UI elements - **Submit** (Blue): - Contains code modification instructions - Positioned at bottom-center, acting as final action point 5. **Color Coding**: - Blue (#0000FF): Primary workflow elements (Thought & Action, Submit) - Red (#FF0000): System feedback (Environment Response) - Yellow (#FFFF00): Code modification section - Gray text in red boxes suggests secondary importance ### Key Observations 1. **Structured Progression**: - Top-to-bottom flow from problem definition (System Prompt) to resolution (Submit) - Left-to-right organization within sections 2. **Color-Coded Workflow**: - Blue dominates (66% of elements), emphasizing active problem-solving - Red (33%) highlights system feedback - Yellow (1 element) draws attention to code changes 3. **Collapsible Elements**: - Environment Responses marked as "collapsed" suggest expandable interface components - Implies iterative interaction between user and system 4. **Code Patch Specificity**: - Shows exact file path and modification instructions - Uses standard git diff format for version control integration ### Interpretation This interface appears designed for collaborative debugging workflows, combining natural language instructions with code modification capabilities. The color coding creates a visual hierarchy that separates: 1. **Problem Definition** (System Prompt) 2. **Example Reference** (Demonstration) 3. **Issue Specification** (Issue Statement) 4. **Interactive Resolution** (Thought/Action ↔ Environment Response) 5. **Implementation** (Submit/Patch) The collapsed environment responses suggest a step-by-step debugging process where users can expand/collapse system feedback as needed. The code patch section's prominent placement indicates that implementation is the final, critical step in the workflow. The use of standard git diff format implies integration with version control systems, making this interface particularly valuable for developers working in collaborative codebases. The layout's strength lies in its clear separation of concerns while maintaining a logical flow. However, the lack of visible text in the Thought & Action and Environment Response sections limits understanding of the specific debugging strategies employed. The interface seems optimized for technical users familiar with both natural language debugging and code modification workflows.