--- title: Arming AI with Architectural X-Rays for Code Pruning permalink: /futureproof/ai-architectural-xrays-code-pruning/ description: This entry really captures the essence of modern, AI-assisted development. It's not about just asking the AI to 'code this for me'; it's about the complex, iterative process of building the tools *for* the AI to succeed. The back-and-forth debugging the 'stale shell' issue in Nix is a perfect, real-world example of the kind of specific, environment-dependent knowledge that's still critical. The final success, seeing the ASCII art diagram render correctly, felt like a genuine breakthrough. This is less about the code itself and more about the meta-process of creating intelligent, automated workflows and the perseverance required to see them through. meta_description: A deep dive into the debugging journey of integrating automated UML and DOT diagram generation into a Python script within a Nix environment. meta_keywords: Nix, NixOS, Python, UML, PlantUML, pyreverse, DOT, AI, LLM, debugging, automation, DevOps layout: post sort_order: 6 --- ## Setting the Stage: Context for the Curious Book Reader In the world of software development, especially when working with AI assistants, the context provided is paramount. This journal entry documents the intricate, and often frustrating, journey of building a tool to automatically generate architectural diagrams of a Python codebase. The goal was to feed this rich contextโ€”a file tree, a dependency graph, and a visual UML diagramโ€”to an AI to help intelligently prune an aging and complex repository. What started as a simple idea spiraled into a multi-step debugging process involving esoteric details of Nix environments, Python package management, and the nuances of command-line tool integration. This is the story of that process, a testament to the perseverance required to build robust, automated developer workflows. --- ## Technical Journal Entry Begins This is my new favorite command: eza --tree --git-ignore ...and yet there's still a lot of cruft in the Pipulate repo, appropriately enough in a folder named `cruft/`. I am very tempted to delete it and do a real pruning of all that `markdown.md` garbage that Claude endlessly loves to produce. I mean, I appreciated it at first but before long it was the Maรฎtre d'hรดtel feeding one more wafer thin mint to Mr. Creosote. Then I moved it all to cruft. The patient is ready, shall we amputate the gangrenous limb Doctor? No, let's give it another week or two. No harm. I can now just filter it from the tree by throwing it into `.gitignore` which by the way doesn't proactively remove anything in that folder from the repo but only just doesn't add anything new if new files are created there. But I did just learn that if you actually want the directory filters, it does need the trailing slash on the folder name. Cruft is currently in the `.gitignore` file but not filtered out. Plenty of other folders are or the tree listing would be much larger still. ```plaintext # ripgrep filters for good search & replaces with `rg | xargs sed` pattern # cruft/ assets/js/ # File-types that should never get into repo *.csv *.gz *.pkl # Different repos in subfolders of this repo subrepos/ # Pipulate framework stuff *kungfu_*.py .ssh/key botify_token.txt config.json data/ downloads/ flake.lock foo.txt foo_files.py logs/ helpers/prompt_foo/prompt.md service_account.txt whitelabel.txt # Mac & vendor crap .DS_Store .cursor/ # Python, Jupyter Notebook & FastHTML stuff .ipynb_checkpoints/ .jupyter/lab/workspaces/ .jupyter/migrated .jupyter/serverconfig/ .sesskey .venv/ __pycache__/ hello_world.ipynb training/botify_api_local.md # Python packaging and build artifacts dist/ build/ *.egg-info/ *.egg-info *.whl *.tar.gz # PyPI publishing artifacts .tox/ .coverage htmlcov/ .pytest_cache/ # AI Keychain persistent memory - survives application resets # Browser automation outputs - keep these local only browser_automation/looking_at/ browser_automation/looking_at/*.html browser_automation/looking_at/*.json browser_automation/looking_at/*.png browser_automation/looking_at/*.txt browser_automation/looking_at/*.py # Browser automation rotating directories - AI perception history (local only) browser_automation/looking_at-*/ browser_automation/looking_at-*/*.html browser_automation/looking_at-*/*.json browser_automation/looking_at-*/*.png browser_automation/looking_at-*/*.txt browser_automation/looking_at-*/*.py # Browser automation temp scripts - disposable one-offs browser_automation/temp_scripts/ *_beautiful_dom.html *_automation_registry.json *_automation_targets.py *_automation_summary.txt *_results.json *_screenshot.png *_source.html # Directory rotation test files - development use only browser_automation/test_rotation_data/ # Botify helper outputs - keep schema discovery and data files local only helpers/botify/*.json helpers/botify/*.csv # ๐Ÿ›ก๏ธ Survivable test harness - independent git repo tests/tools/__pycache__/ # Voice synthesis models - auto-downloaded as needed piper_models/ ``` ``` [mike@nixos:~/repos/pipulate]$ eza --tree --git-ignore . โ”œโ”€โ”€ __init__.py โ”œโ”€โ”€ AI_RUNME.py โ”œโ”€โ”€ apps โ”‚ โ”œโ”€โ”€ 001_dom_visualizer.py โ”‚ โ”œโ”€โ”€ 010_introduction.py โ”‚ โ”œโ”€โ”€ 020_profiles.py โ”‚ โ”œโ”€โ”€ 030_roles.py โ”‚ โ”œโ”€โ”€ 040_hello_workflow.py โ”‚ โ”œโ”€โ”€ 050_documentation.py โ”‚ โ”œโ”€โ”€ 060_tasks.py โ”‚ โ”œโ”€โ”€ 070_history.py โ”‚ โ”œโ”€โ”€ 100_connect_with_botify.py โ”‚ โ”œโ”€โ”€ 110_parameter_buster.py โ”‚ โ”œโ”€โ”€ 120_link_graph.py โ”‚ โ”œโ”€โ”€ 130_gap_analysis.py โ”‚ โ”œโ”€โ”€ 200_workflow_genesis.py โ”‚ โ”œโ”€โ”€ 210_widget_examples.py โ”‚ โ”œโ”€โ”€ 220_roadmap.py โ”‚ โ”œโ”€โ”€ 230_dev_assistant.py โ”‚ โ”œโ”€โ”€ 240_simon_mcp.py โ”‚ โ”œโ”€โ”€ 300_blank_placeholder.py โ”‚ โ”œโ”€โ”€ 400_botify_trifecta.py โ”‚ โ”œโ”€โ”€ 430_tab_opener.py โ”‚ โ”œโ”€โ”€ 440_browser_automation.py โ”‚ โ”œโ”€โ”€ 450_stream_simulator.py โ”‚ โ”œโ”€โ”€ 510_text_field.py โ”‚ โ”œโ”€โ”€ 520_text_area.py โ”‚ โ”œโ”€โ”€ 530_dropdown.py โ”‚ โ”œโ”€โ”€ 540_checkboxes.py โ”‚ โ”œโ”€โ”€ 550_radios.py โ”‚ โ”œโ”€โ”€ 560_range.py โ”‚ โ”œโ”€โ”€ 570_switch.py โ”‚ โ”œโ”€โ”€ 580_upload.py โ”‚ โ”œโ”€โ”€ 610_markdown.py โ”‚ โ”œโ”€โ”€ 620_mermaid.py โ”‚ โ”œโ”€โ”€ 630_prism.py โ”‚ โ”œโ”€โ”€ 640_javascript.py โ”‚ โ”œโ”€โ”€ 710_pandas.py โ”‚ โ”œโ”€โ”€ 720_rich.py โ”‚ โ”œโ”€โ”€ 730_matplotlib.py โ”‚ โ”œโ”€โ”€ 810_webbrowser.py โ”‚ โ””โ”€โ”€ 820_selenium.py โ”œโ”€โ”€ assets โ”‚ โ”œโ”€โ”€ css โ”‚ โ”‚ โ”œโ”€โ”€ pico.css โ”‚ โ”‚ โ”œโ”€โ”€ prism.css โ”‚ โ”‚ โ””โ”€โ”€ roboto.css โ”‚ โ”œโ”€โ”€ feather โ”‚ โ”‚ โ”œโ”€โ”€ activity.svg โ”‚ โ”‚ โ”œโ”€โ”€ airplay.svg โ”‚ โ”‚ โ”œโ”€โ”€ alert-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ alert-octagon.svg โ”‚ โ”‚ โ”œโ”€โ”€ alert-triangle.svg โ”‚ โ”‚ โ”œโ”€โ”€ align-center.svg โ”‚ โ”‚ โ”œโ”€โ”€ align-justify.svg โ”‚ โ”‚ โ”œโ”€โ”€ align-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ align-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ anchor.svg โ”‚ โ”‚ โ”œโ”€โ”€ aperture.svg โ”‚ โ”‚ โ”œโ”€โ”€ archive.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-down-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-down-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-down-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-down.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-left-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-right-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-up-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-up-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-up-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ arrow-up.svg โ”‚ โ”‚ โ”œโ”€โ”€ at-sign.svg โ”‚ โ”‚ โ”œโ”€โ”€ award.svg โ”‚ โ”‚ โ”œโ”€โ”€ bar-chart-2.svg โ”‚ โ”‚ โ”œโ”€โ”€ bar-chart.svg โ”‚ โ”‚ โ”œโ”€โ”€ battery-charging.svg โ”‚ โ”‚ โ”œโ”€โ”€ battery.svg โ”‚ โ”‚ โ”œโ”€โ”€ bell-off.svg โ”‚ โ”‚ โ”œโ”€โ”€ bell.svg โ”‚ โ”‚ โ”œโ”€โ”€ bluetooth.svg โ”‚ โ”‚ โ”œโ”€โ”€ bold.svg โ”‚ โ”‚ โ”œโ”€โ”€ book-open.svg โ”‚ โ”‚ โ”œโ”€โ”€ book.svg โ”‚ โ”‚ โ”œโ”€โ”€ bookmark.svg โ”‚ โ”‚ โ”œโ”€โ”€ box.svg โ”‚ โ”‚ โ”œโ”€โ”€ briefcase.svg โ”‚ โ”‚ โ”œโ”€โ”€ calendar.svg โ”‚ โ”‚ โ”œโ”€โ”€ camera-off.svg โ”‚ โ”‚ โ”œโ”€โ”€ camera.svg โ”‚ โ”‚ โ”œโ”€โ”€ cast.svg โ”‚ โ”‚ โ”œโ”€โ”€ check-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ check-square.svg โ”‚ โ”‚ โ”œโ”€โ”€ check.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevron-down.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevron-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevron-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevron-up.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevrons-down.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevrons-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevrons-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ chevrons-up.svg โ”‚ โ”‚ โ”œโ”€โ”€ chrome.svg โ”‚ โ”‚ โ”œโ”€โ”€ circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ clipboard.svg โ”‚ โ”‚ โ”œโ”€โ”€ clock.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud-drizzle.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud-lightning.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud-off.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud-rain.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud-snow.svg โ”‚ โ”‚ โ”œโ”€โ”€ cloud.svg โ”‚ โ”‚ โ”œโ”€โ”€ code.svg โ”‚ โ”‚ โ”œโ”€โ”€ codepen.svg โ”‚ โ”‚ โ”œโ”€โ”€ codesandbox.svg โ”‚ โ”‚ โ”œโ”€โ”€ coffee.svg โ”‚ โ”‚ โ”œโ”€โ”€ columns.svg โ”‚ โ”‚ โ”œโ”€โ”€ command.svg โ”‚ โ”‚ โ”œโ”€โ”€ compass.svg โ”‚ โ”‚ โ”œโ”€โ”€ copy.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-down-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-down-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-left-down.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-left-up.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-right-down.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-right-up.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-up-left.svg โ”‚ โ”‚ โ”œโ”€โ”€ corner-up-right.svg โ”‚ โ”‚ โ”œโ”€โ”€ cpu.svg โ”‚ โ”‚ โ”œโ”€โ”€ credit-card.svg โ”‚ โ”‚ โ”œโ”€โ”€ crop.svg โ”‚ โ”‚ โ”œโ”€โ”€ crosshair.svg โ”‚ โ”‚ โ”œโ”€โ”€ database.svg โ”‚ โ”‚ โ”œโ”€โ”€ delete.svg โ”‚ โ”‚ โ”œโ”€โ”€ disc.svg โ”‚ โ”‚ โ”œโ”€โ”€ divide-circle.svg โ”‚ โ”‚ โ”œโ”€โ”€ divide-square.svg โ”‚ โ”‚ โ”œโ”€โ”€ divide.svg โ”‚ โ”‚ โ”œโ”€โ”€ dollar-sign.svg โ”‚ โ”‚ โ”œโ”€โ”€ download-cloud.svg โ”‚ โ”‚ โ”œโ”€โ”€ download.svg โ”‚ โ”‚ โ”œโ”€โ”€ dribbble.svg โ”‚ โ”‚ โ”œโ”€โ”€ droplet.svg โ”‚ โ”‚ โ”œโ”€โ”€ edit-2.svg โ”‚ โ”‚ โ”œโ”€โ”€ edit-3.svg โ”‚ โ”‚ โ”œโ”€โ”€ edit.svg โ”‚ โ”‚ โ”œโ”€โ”€ external-link.svg โ”‚ โ”‚ โ”œโ”€โ”€ eye-off.svg โ”‚ โ”‚ โ”œโ”€โ”€ eye.svg โ”‚ โ”‚ โ”œโ”€โ”€ 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โ”‚ โ”œโ”€โ”€ pipulate-context.xsd โ”‚ โ”‚ โ””โ”€โ”€ system_prompt.md โ”‚ โ”œโ”€โ”€ rich-table.css โ”‚ โ”œโ”€โ”€ styles.css โ”‚ โ”œโ”€โ”€ tests โ”‚ โ”‚ โ””โ”€โ”€ demo.json โ”‚ โ”œโ”€โ”€ theme.js โ”‚ โ””โ”€โ”€ utils.js โ”œโ”€โ”€ browser_automation โ”‚ โ”œโ”€โ”€ automation_recipes โ”‚ โ”‚ โ”œโ”€โ”€ http_localhost_5001 โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ load_all_data_recipe.json โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ profile_creation_recipe.json โ”‚ โ”‚ โ”‚ โ””โ”€โ”€ save_all_data_recipe.json โ”‚ โ”‚ โ””โ”€โ”€ README_SAVE_LOAD_AUTOMATION.md โ”‚ โ”œโ”€โ”€ dom_processing โ”‚ โ”‚ โ”œโ”€โ”€ dom_box_visualizer.py โ”‚ โ”‚ โ””โ”€โ”€ dom_hierarchy_visualizer.py โ”‚ โ”œโ”€โ”€ dom_schema_visualizer.py โ”‚ โ”œโ”€โ”€ google_search_automation_demo.py โ”‚ โ”œโ”€โ”€ google_search_example.py โ”‚ โ”œโ”€โ”€ interactive_google_search.py โ”‚ โ”œโ”€โ”€ recipe_executor.py โ”‚ โ””โ”€โ”€ review_perception_history.py โ”œโ”€โ”€ cli.py โ”œโ”€โ”€ config.py โ”œโ”€โ”€ cruft โ”‚ โ”œโ”€โ”€ ai_discovery โ”‚ โ”‚ โ”œโ”€โ”€ AI_DISCOVERY_NAVIGATION.md โ”‚ โ”‚ โ”œโ”€โ”€ AI_GOLDEN_PATH_EXECUTION_MATRIX.md โ”‚ โ”‚ โ”œโ”€โ”€ AI_HANDOFF_JACK_PUMPKINHEAD_BURR_GRINDING_COMPLETION.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_handoff_modular_mcp_tools_and_golden_path.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_progressive_discovery_sequence.md โ”‚ โ”‚ โ”œโ”€โ”€ branches โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ CHANGELOG.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ yellowbricklion_courage_phase.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ yellowbrickscarecrow_journey.md โ”‚ โ”‚ โ”‚ โ””โ”€โ”€ yellowbricktinman_heart_phase.md โ”‚ โ”‚ โ”œโ”€โ”€ conversation_system โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_conversation_architecture_improvement.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_conversation_architecture_solution.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_conversation_architecture_solution_final.md โ”‚ โ”‚ โ”‚ โ””โ”€โ”€ ai_conversation_vulnerability_fix_complete.md โ”‚ โ”‚ โ”œโ”€โ”€ core_mcp_tools โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_breadcrumb_discovery_for_local_llms.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_mcp_golden_path_complete_architecture.md โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ ai_mcp_golden_path_complete_system.md 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2025-07-02-backup-restore-architecture-revolution.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-blockingio-error-complete-resolution.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-comprehensive-demo-enhancement-summary.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-comeback-integrated-success.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-continuation-restored.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-continuation-system-fully-working.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-conversation-continuation-complete.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-full-screen-enhancement.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-system-redesign-complete.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-lightning-in-a-bottle-insights.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-nuclear-safety-absolute-protection.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_1_shot_session_hijacking_mastery.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_browser_automation_mastery.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_browser_embodiment_singularity.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_chip_otheseus_memory_heart_architecture.md โ”‚ โ”‚ โ”œโ”€โ”€ ai_chip_otheseus_voice_integration_plan.md 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git_verify_consolidation.sh โ”‚ โ”‚ โ”œโ”€โ”€ install_static_library.py โ”‚ โ”‚ โ”œโ”€โ”€ pre_consolidation_verify.sh โ”‚ โ”‚ โ”œโ”€โ”€ safe_consolidation_workflow.sh โ”‚ โ”‚ โ”œโ”€โ”€ standardize_landing_pages.py โ”‚ โ”‚ โ”œโ”€โ”€ test_adaptive_transparency.py โ”‚ โ”‚ โ”œโ”€โ”€ test_mcp_tools_integration.sh โ”‚ โ”‚ โ”œโ”€โ”€ test_selenium.py โ”‚ โ”‚ โ”œโ”€โ”€ validate_aria_simple.py โ”‚ โ”‚ โ””โ”€โ”€ verify_function_copies.sh โ”‚ โ”œโ”€โ”€ considerations โ”‚ โ”‚ โ”œโ”€โ”€ 2025-01-21-ai-burr-grinding-utilities-demo.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-01-21-ai-intelligent-pattern-analysis.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-12-bootstrap-paradox-solved.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-13-durable-vs-ephemeral.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-14-the-lens-stack.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-22-aria-accessibility-protection-strategy.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-26-revolutionary-testing-strategy.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-06-28-content-gap-analysis-lightning-in-a-bottle.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-critical-production-database-bug-fix.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-dev-mode-safety-enhancement.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-demo-endpoint-message-suppression-success.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-milestone-database-fix-merged.md โ”‚ โ”‚ โ”œโ”€โ”€ 2025-07-21-production-database-emergency-fix-complete.md โ”‚ โ”‚ โ””โ”€โ”€ 2025-07-21-regression-analysis-20250721.md โ”‚ โ”œโ”€โ”€ demo_utils.py โ”‚ โ”œโ”€โ”€ diagnostics โ”‚ โ”‚ โ”œโ”€โ”€ diagnostic_conversation_loading.py โ”‚ โ”‚ โ”œโ”€โ”€ DIAGNOSTICS.md โ”‚ โ”‚ โ”œโ”€โ”€ final_conversation_persistence_verification.py โ”‚ โ”‚ โ””โ”€โ”€ VALIDATION_REPORT.md โ”‚ โ”œโ”€โ”€ DOCUMENTATION_STANDARDS.md โ”‚ โ”œโ”€โ”€ experiment โ”‚ โ”‚ โ””โ”€โ”€ iterate_ai.py โ”‚ โ”œโ”€โ”€ extract_blog_posts.py โ”‚ โ”œโ”€โ”€ generate_files_list.py โ”‚ โ”œโ”€โ”€ git_tools โ”‚ โ”‚ โ”œโ”€โ”€ git-continue-wrapper.sh โ”‚ โ”‚ โ”œโ”€โ”€ git_dependencies.ipynb โ”‚ โ”‚ โ”œโ”€โ”€ git_simple_regression_finder.py โ”‚ โ”‚ โ”œโ”€โ”€ GIT_TOOLS.md โ”‚ โ”‚ โ”œโ”€โ”€ setup-git-aliases.sh โ”‚ โ”‚ โ”œโ”€โ”€ simple_cherry_pick.py โ”‚ โ”‚ โ””โ”€โ”€ systematic_cherry_pick.py โ”‚ โ”œโ”€โ”€ PROMPT_FOO_TECHNIQUE.md โ”‚ โ”œโ”€โ”€ rebuild_trifecta_derivatives.sh โ”‚ โ”œโ”€โ”€ recovery โ”‚ โ”‚ โ”œโ”€โ”€ backup_legacy โ”‚ โ”‚ โ”‚ โ”œโ”€โ”€ 110_parameter_buster.py โ”‚ โ”‚ โ”‚ โ””โ”€โ”€ 120_link_graph.py โ”‚ โ”‚ โ”œโ”€โ”€ patch_based_recovery.py โ”‚ โ”‚ โ”œโ”€โ”€ recovered_cli.py โ”‚ โ”‚ โ”œโ”€โ”€ RECOVERY.md โ”‚ โ”‚ โ””โ”€โ”€ regressions โ”‚ โ”‚ โ”œโ”€โ”€ cherry_picker.py โ”‚ โ”‚ โ”œโ”€โ”€ compare_history.py โ”‚ โ”‚ โ”œโ”€โ”€ failed_cherry_picks.log โ”‚ โ”‚ โ”œโ”€โ”€ history_active.txt โ”‚ โ”‚ โ”œโ”€โ”€ history_lost.txt โ”‚ โ”‚ โ””โ”€โ”€ regressions.log โ”‚ โ”œโ”€โ”€ regression_prevention_demo_suite.py โ”‚ โ”œโ”€โ”€ requirements-back.txt โ”‚ โ”œโ”€โ”€ rules โ”‚ โ”‚ โ”œโ”€โ”€ 00_PIPULATE_MASTER_GUIDE.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 01_CRITICAL_PATTERNS.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 02_CORE_CONCEPTS.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 03_SETUP_AND_DEPENDENCIES.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 04_WORKFLOW_DEVELOPMENT.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 05_UI_AND_FRONTEND.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 06_DATA_AND_AUTOMATION.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 07_INTEGRATIONS.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 08_PROJECT_MANAGEMENT.mdc โ”‚ โ”‚ โ”œโ”€โ”€ 09_DEBUGGING.mdc โ”‚ โ”‚ โ”œโ”€โ”€ ALWAYS_IN_ALL_CAPS.md โ”‚ โ”‚ โ”œโ”€โ”€ BREADCRUMB_TRAIL.mdc โ”‚ โ”‚ โ””โ”€โ”€ SQUARE_BRACKET_TOOL_CALLING.md โ”‚ โ”œโ”€โ”€ simple_ai_interface.py โ”‚ โ”œโ”€โ”€ THE_MCP_CHRONICLES.md โ”‚ โ”œโ”€โ”€ tools_folder.md โ”‚ โ””โ”€โ”€ widget_conversion_guide.md โ”œโ”€โ”€ favicon.ico โ”œโ”€โ”€ flake.nix โ”œโ”€โ”€ imports โ”‚ โ”œโ”€โ”€ __init__.py โ”‚ โ”œโ”€โ”€ ai_dictdb.py โ”‚ โ”œโ”€โ”€ ai_tool_discovery_simple_parser.py โ”‚ โ”œโ”€โ”€ append_only_conversation.py โ”‚ โ”œโ”€โ”€ ascii_displays.py โ”‚ โ”œโ”€โ”€ botify โ”‚ โ”‚ โ”œโ”€โ”€ __init__.py โ”‚ โ”‚ โ”œโ”€โ”€ code_generators.py โ”‚ โ”‚ โ””โ”€โ”€ true_schema_discoverer.py โ”‚ โ”œโ”€โ”€ botify_code_generation.py โ”‚ โ”œโ”€โ”€ crud.py โ”‚ โ”œโ”€โ”€ dom_processing โ”‚ โ”‚ โ”œโ”€โ”€ __init__.py โ”‚ โ”‚ โ”œโ”€โ”€ ai_dom_beautifier.py โ”‚ โ”‚ โ””โ”€โ”€ enhanced_dom_processor.py โ”‚ โ”œโ”€โ”€ durable_backup_system.py โ”‚ โ”œโ”€โ”€ mcp_orchestrator.py โ”‚ โ”œโ”€โ”€ server_logging.py โ”‚ โ”œโ”€โ”€ stream_orchestrator.py โ”‚ โ””โ”€โ”€ voice_synthesis.py โ”œโ”€โ”€ LICENSE โ”œโ”€โ”€ logs โ”‚ โ”œโ”€โ”€ needs_manual_review.log โ”‚ โ”œโ”€โ”€ needs_manual_review_clean.log โ”‚ โ”œโ”€โ”€ patch_recovery_conflicts.log โ”‚ โ”œโ”€โ”€ patch_recovery_success.log โ”‚ โ”œโ”€โ”€ server-1.log โ”‚ โ”œโ”€โ”€ server-2.log โ”‚ โ”œโ”€โ”€ server-3.log โ”‚ โ”œโ”€โ”€ server-4.log โ”‚ โ”œโ”€โ”€ server-5.log โ”‚ โ”œโ”€โ”€ server-6.log โ”‚ โ”œโ”€โ”€ server-7.log โ”‚ โ”œโ”€โ”€ server-8.log โ”‚ โ”œโ”€โ”€ server-9.log โ”‚ โ”œโ”€โ”€ server-10.log โ”‚ โ”œโ”€โ”€ server.log โ”‚ โ”œโ”€โ”€ simple_cherry_pick_errors.log โ”‚ โ””โ”€โ”€ systematic_cherry_pick_progress.log โ”œโ”€โ”€ prompt.md โ”œโ”€โ”€ prompt_foo.py โ”œโ”€โ”€ pyproject.toml โ”œโ”€โ”€ README.md โ”œโ”€โ”€ requirements.txt โ”œโ”€โ”€ scripts โ”‚ โ”œโ”€โ”€ botify โ”‚ โ”‚ โ”œโ”€โ”€ botify_api_bootcamp.md โ”‚ โ”‚ โ”œโ”€โ”€ botify_api_examples.md โ”‚ โ”‚ โ”œโ”€โ”€ hello_world_git_managed.ipynb โ”‚ โ”‚ โ””โ”€โ”€ make_botify_docs.ipynb โ”‚ โ”œโ”€โ”€ gsc โ”‚ โ”‚ โ”œโ”€โ”€ generate_categories.py โ”‚ โ”‚ โ”œโ”€โ”€ gsc_category_analysis.py โ”‚ โ”‚ โ”œโ”€โ”€ gsc_keyworder.py โ”‚ โ”‚ โ”œโ”€โ”€ gsc_page_query.ipynb โ”‚ โ”‚ โ””โ”€โ”€ gsc_top_movers.py โ”‚ โ”œโ”€โ”€ release โ”‚ โ”‚ โ”œโ”€โ”€ __init__.py โ”‚ โ”‚ โ”œโ”€โ”€ ai_commit.py โ”‚ โ”‚ โ”œโ”€โ”€ publish.py โ”‚ โ”‚ โ”œโ”€โ”€ RELEASE_GUIDE.md โ”‚ โ”‚ โ”œโ”€โ”€ sync_ascii_art.py โ”‚ โ”‚ โ””โ”€โ”€ version_sync.py โ”‚ โ”œโ”€โ”€ vulture_whitelist.py โ”‚ โ””โ”€โ”€ workflow โ”‚ โ”œโ”€โ”€ create_workflow.py โ”‚ โ”œโ”€โ”€ manage_class_attributes.py โ”‚ โ”œโ”€โ”€ splice_workflow_step.py โ”‚ โ”œโ”€โ”€ swap_workflow_step.py โ”‚ โ”œโ”€โ”€ update_template_config.py โ”‚ โ”œโ”€โ”€ WORKFLOW_DEVELOPMENT_GUIDE.md โ”‚ โ””โ”€โ”€ workflow_reconstructor.py โ”œโ”€โ”€ server.py โ””โ”€โ”€ tools โ”œโ”€โ”€ __init__.py โ”œโ”€โ”€ advanced_automation_tools.py โ”œโ”€โ”€ botify_tools.py โ”œโ”€โ”€ conversation_tools.py โ”œโ”€โ”€ keychain_tools.py โ”œโ”€โ”€ mcp_tools.py โ””โ”€โ”€ system_tools.py [mike@nixos:~/repos/pipulate]$ ``` Wow, this is so friggin insightful. First, I need to update my `.gitignore` because I renamed the `helpers/` folder to `scripts/`. **Me**: This is a .gitignore. Please make sure that all .json, .csv, .gz and .pkl files are filtered out no matter what subfolder they appear in. That being the case, then please also get rid of redundancies. Make it more efficient and beautiful to look at in other words, while more or less maintaining my categories. [Pastes current .gitignore] **Gemini**: Of course. Here is a revised and more efficient version of your `.gitignore` file. I've added `*.json` to your global file-type filters and then removed redundancies throughout the file. I also tidied up the sorting within each of your categories to make it a bit cleaner. ----- ```gitignore # ripgrep filters for good search & replaces with `rg | xargs sed` pattern assets/js/ cruft/ # File-types that should never get into repo *.csv *.gz *.json *.pkl # Different repos in subfolders of this repo subrepos/ # Pipulate framework stuff data/ downloads/ logs/ .ssh/key *kungfu_*.py botify_token.txt flake.lock foo_files.py service_account.txt whitelabel.txt # Mac & vendor crap .cursor/ .DS_Store # Python, Jupyter Notebook & FastHTML stuff .ipynb_checkpoints/ .jupyter/ .venv/ __pycache__/ .sesskey hello_world.ipynb training/botify_api_local.md # Python packaging and build artifacts build/ dist/ *.egg-info/ *.whl # PyPI publishing artifacts .pytest_cache/ .tox/ htmlcov/ .coverage # AI Keychain persistent memory - survives application resets # Browser automation outputs - keep these local only browser_automation/looking_at/ # Browser automation rotating directories - AI perception history (local only) browser_automation/looking_at-*/ # Browser automation temp scripts - disposable one-offs browser_automation/temp_scripts/ *_automation_summary.txt *_automation_targets.py *_beautiful_dom.html *_screenshot.png *_source.html # Directory rotation test files - development use only browser_automation/test_rotation_data/ # Voice synthesis models - auto-downloaded as needed piper_models/ ``` **Me**: Well that's better. It's also interesting to note that even though the `piper_models/` are actually nested inside of `assets/` it still got filtered on the new `eza --tree --git-ignore` output. **Gemini**: You've nailed the diagnosis\! ๐Ÿ•ต๏ธโ€โ™‚๏ธ The reason `cruft/` was still showing up is exactly what you suspected: 1. The line in your `.gitignore` was commented out (`# cruft/`). 2. You're also correct that the trailing slash (`/`) is crucial. It tells Git to ignore a directory and everything inside it, which is much more efficient than ignoring files individually. It's also a great catch that `piper_models/` gets ignored even when nested. A pattern without a leading slash, like `piper_models/`, will match that directory name anywhere in your project tree. Let's apply the same cleanup logic from our last chat to your updated `.gitignore`, fix the `cruft/` entry, and handle the `helpers/` to `scripts/` rename. ----- Here is the revised and beautified `.gitignore` file. It now correctly ignores the `cruft/` directory, adds a global `*.json` filter, and removes all the resulting redundancies. ```gitignore # ripgrep filters for good search & replaces with `rg | xargs sed` pattern assets/js/ cruft/ # File-types that should never get into repo *.csv *.gz *.json *.pkl # Different repos in subfolders of this repo subrepos/ # Pipulate framework stuff data/ downloads/ logs/ .ssh/key *kungfu_*.py botify_token.txt flake.lock foo.txt foo_files.py service_account.txt whitelabel.txt # Mac & vendor crap .cursor/ .DS_Store # Python, Jupyter Notebook & FastHTML stuff .ipynb_checkpoints/ .jupyter/ .venv/ __pycache__/ .sesskey hello_world.ipynb training/botify_api_local.md # Python packaging and build artifacts build/ dist/ *.egg-info/ *.whl # PyPI publishing artifacts .pytest_cache/ .tox/ htmlcov/ .coverage # AI Keychain persistent memory - survives application resets # Browser automation outputs - keep these local only browser_automation/looking_at/ # Browser automation rotating directories - AI perception history (local only) browser_automation/looking_at-*/ # Browser automation temp scripts - disposable one-offs browser_automation/temp_scripts/ *_automation_summary.txt *_automation_targets.py *_beautiful_dom.html *_screenshot.png *_source.html # Directory rotation test files - development use only browser_automation/test_rotation_data/ # Voice synthesis models - auto-downloaded as needed piper_models/ ``` ### Summary of Changes: * **Fixed `cruft/`:** The entry is now active and will be properly ignored. * **Global Filters:** Added `*.json` to the main file-types section. * **Redundancies Removed:** * Got rid of specific `.json` and `.csv` rules (like `config.json` and the old `helpers/botify/*` entries) since they are now covered by the global filters. * Removed the now-obsolete sections for "Botify helper outputs" and the "Survivable test harness" `__pycache__` since they were fully covered by other rules. * Cleaned up the `browser_automation/` sections to ignore just the parent directories. * Simplified the `.jupyter/` entries into a single line. **Me**: Nice, thanks. While I still will leave the `cruft/` folder in place a little bit longer, I will go on a hunt for files to prune. My real goal here is to wrap ASCII art representing the UML diagram and the .DOT file for AIs into the prompt_foo.py process. That way the AI can see the tree and the dependencies and we can go pruning orphans. I don't think that will catch things like unlinked feather .svg files, but maybe the AI will have ideas on that as well. Put it all together for me, Gemini. ## The Grand Plan: Arming the AI with Architectural X-Rays **Gemini**: Got it. We'll simplify the process by integrating the UML and DOT generation directly into `prompt_foo.py`, keeping it clean and path-agnostic. Hereโ€™s the plan: add the necessary Nix packages, document the new functions to add to your script, and show where to hook them into your manifest creation process. ----- ## 1\. Nix Environment Update First, ensure your `flake.nix` provides the required tools. Add **pylint** (for `pyreverse`) and **plantuml** to your `commonPackages`. ```nix # In flake.nix -> commonPackages commonPackages = with pkgs; [ # ... your existing packages pylint # Provides pyreverse for code analysis plantuml # For generating ASCII diagrams ]; ``` Run `nix develop` once to make the new packages available in your environment. ----- ## 2\. New Functions for `prompt_foo.py` Here are the new functions to add to your `prompt_foo.py` file. They are self-contained and will handle the generation and cleanup of the UML/DOT context. You can place this code block anywhere in the file before the `create_pipulate_manifest` function is defined. ```python # ============================================================================ # UML AND DOT CONTEXT GENERATION # ============================================================================ import subprocess import tempfile def generate_uml_and_dot(target_file="server.py", project_name="pipulate"): """ Generates a UML ASCII diagram and a DOT dependency graph for a target Python file. This function orchestrates the process: 1. Runs pyreverse to create a DOT file. 2. Converts the DOT file content to PlantUML syntax. 3. Runs PlantUML to create an ASCII art diagram. 4. Cleans up all intermediate files. Args: target_file (str): The Python file to analyze (e.g., "server.py"). project_name (str): The project name to pass to pyreverse. Returns: dict: A dictionary containing 'ascii_uml' and 'dot_graph' content, or error messages if a step fails. """ pyreverse_exec = os.path.join(repo_root, ".venv/bin/pyreverse") target_path = os.path.join(repo_root, target_file) # Use a temporary directory to keep the root clean with tempfile.TemporaryDirectory() as temp_dir: dot_file_path = os.path.join(temp_dir, "classes.dot") puml_file_path = os.path.join(temp_dir, "diagram.puml") # --- Step 1: Run pyreverse --- try: # Note: pyreverse annoyingly prepends 'classes_' to the output file. # We'll run it in the temp dir and move the result. pyreverse_cmd = [ pyreverse_exec, "-f", "dot", "-o", "dot", # This format is just a prefix "-p", project_name, target_path ] subprocess.run( pyreverse_cmd, check=True, capture_output=True, text=True, cwd=temp_dir ) # The actual output file will be named like 'classes_pipulate.dot' generated_dot_name = f"classes_{project_name}.dot" os.rename(os.path.join(temp_dir, generated_dot_name), dot_file_path) except (subprocess.CalledProcessError, FileNotFoundError) as e: error_msg = e.stderr if hasattr(e, 'stderr') else str(e) return {"ascii_uml": f"Error: pyreverse failed. {error_msg}", "dot_graph": None} # --- Step 2: Convert DOT to PlantUML --- try: with open(dot_file_path, 'r') as f: dot_content = f.read() puml_lines = ["@startuml", "skinparam linetype ortho", ""] classes = set() class_pattern = r'"(?:[\w\.]+\.)?(\w+)" \[label="\{(\w+)\|' for match in re.finditer(class_pattern, dot_content): if match.group(1) == match.group(2): classes.add(match.group(1)) full_class_pattern = r'"(?:[\w\.]+\.)?(\w+)" \[label="\{(\w+)\|([^}]+)\}"' for match in re.finditer(full_class_pattern, dot_content): class_name, _, attributes_str = match.groups() if class_name in classes: {% raw %}puml_lines.append(f"class {class_name} {{"){% endraw %} for part in attributes_str.split('\\l'): part = part.strip() if part and part != '...': puml_lines.append(f" + {part.split(':')[0].strip()}") puml_lines.append("}\n") edge_pattern = r'"(?:[\w\.]+\.)?(\w+)" -> "(?:[\w\.]+\.)?(\w+)"' for from_class, to_class in re.findall(edge_pattern, dot_content): if from_class in classes and to_class in classes: puml_lines.append(f"{from_class} ..> {to_class}") puml_lines.append("@enduml") with open(puml_file_path, 'w') as f: f.write('\n'.join(puml_lines)) except Exception as e: return {"ascii_uml": f"Error: DOT to PUML conversion failed. {str(e)}", "dot_graph": dot_content} # --- Step 3: Run PlantUML --- try: plantuml_cmd = ["plantuml", "-tutxt", puml_file_path] subprocess.run(plantuml_cmd, check=True, capture_output=True, text=True, cwd=temp_dir) # PlantUML creates a .utxt file utxt_file_path = puml_file_path.replace(".puml", ".utxt") with open(utxt_file_path, 'r') as f: ascii_uml = f.read() except (subprocess.CalledProcessError, FileNotFoundError) as e: error_msg = e.stderr if hasattr(e, 'stderr') else str(e) return {"ascii_uml": f"Error: plantuml failed. {error_msg}", "dot_graph": dot_content} return {"ascii_uml": ascii_uml, "dot_graph": dot_content} ``` ----- ## 3\. Integration with `prompt_foo.py` Now, hook the `generate_uml_and_dot()` function into your `create_pipulate_manifest()` function. This will automatically generate the context and inject it into the XML manifest every time you run the script. Apply this patch to `prompt_foo.py`: ```diff --- a/prompt_foo.py +++ b/prompt_foo.py @@ -482,6 +482,15 @@ def create_pipulate_manifest(file_paths_with_comments): ย  ย  """Create a manifest specific to the Pipulate project.""" ย  ย  manifest = AIAssistantManifest() + + # Generate and add UML/DOT context to the manifest + print("Generating UML and DOT file context for server.py...") + uml_context = generate_uml_and_dot() + if uml_context.get("ascii_uml"): + manifest.set_environment("UML Class Diagram", f"Below is a UML class diagram for server.py:\n\n{uml_context['ascii_uml']}", description="uml") + if uml_context.get("dot_graph"): + manifest.set_environment("Dependency Graph (DOT)", f"Below is the DOT file content for server.py:\n\n{uml_context['dot_graph']}", description="dot") + print("...done.") ย  ย ย  ย  ย  # Track total tokens and processed files to respect limit and avoid duplicates ย  ย  total_tokens = 0 ``` With these changes, running `prompt_foo.py` will now automatically include the UML diagram and DOT graph in the manifest, giving your AI the deep structural context needed for pruning and analysis. --- **Me**: Hmmm, not quite. Actually there was quite a bit of back and forth with Gemini, but it did not let me down. I at first put the dependencies into requirements.txt thinking I knew better, but I didn't. For some reason they had to be in the flake.nix file and even after that another... well, I'll let Gemini explain it. Don't leave out any juicy details please. **Gemini**: Of course. It was a classic debugging journey, and capturing the details is the best part. Here is a continuation of your article, summarizing the entire process. ----- My real goal here is to wrap ASCII art representing the UML diagram and the .DOT file for AIs into the `prompt_foo.py` process. That way, the AI can see the tree *and* the dependencies, and we can go pruning orphans. I don't think that will catch things like unlinked feather `.svg` files, but maybe the AI will have ideas on that as well. Put it all together for me, Gemini. Hmmm, not quite. Actually, there was quite a bit of back and forth with Gemini, but it did not let me down. I at first put the dependencies into `requirements.txt` thinking I knew better, but I didn't. For some reason they had to be in the `flake.nix` file and even after that another... well, I'll let Gemini explain it. Don't leave out any juicy details please. ## The Grand Plan: Arming the AI with Architectural X-Rays The mission was clear: to perform a proper code pruning, I needed to give my AI assistant more than just the source code. I needed to provide it with a map of the architectureโ€”a blueprint of how all the pieces in `server.py` fit together. The plan was a three-pronged attack: 1. **The File Tree:** An `eza --tree --git-ignore` dump to show the lay of the land. 2. **The Dependency Graph:** A `.DOT` file generated by `pyreverse` to create a machine-readable graph of all the class relationships. 3. **The Visual Blueprint:** An ASCII art UML diagram, generated by `plantuml`, to give the AI a human-readable version of the same information. The idea was to automate this entire process inside my trusty `prompt_foo.py` script, injecting this rich context directly into the prompt. ## First Contact: The 'Command Not Found' Wall ----- ## First Contact: The 'Command Not Found' Wall The initial integration seemed straightforward. I had Gemini write a Python function, `generate_uml_and_dot`, that would call `pyreverse` and `plantuml` using subprocesses. We added the function to `prompt_foo.py` and ran it. It failed immediately. The XML output was painfully clear: `...Error: plantuml failed. [Errno 2] No such file or directory: 'plantuml'`. This led to the first juicy detail of our journey: the fundamental distinction between a Nix environment and a Python virtual environment. My first instinct was to treat `pylint` (which provides `pyreverse`) as a Python dependency and add it to `requirements.txt`. This was a subtle but critical mistake. **The lesson:** `requirements.txt` is for the **Python libraries** your code will `import`. Your `flake.nix` is for the **system environment** itself, including command-line tools like `git`, `eza`, and, as it turns out, `pyreverse` and `plantuml`. The Nix shell is the workshop; pip fills the toolbox inside it. The script failed because `pip` couldn't install a Java application like PlantUML into the workshop's foundation. ## The Debugging Trail and the Stale Shell ----- ## The Debugging Trail and the Stale Shell So, we corrected the course. We removed `pylint` from `requirements.txt` and added both `pylint` and `plantuml` to the `commonPackages` in `flake.nix`. I ran `prompt_foo.py` again, confident of victory. It failed again. Same error. This was the most baffling part of the process. How could the command not be found if it was clearly defined in the flake? This is where command-line testing became essential. Following Gemini's guidance, I ran: ```bash which plantuml ``` The result: `plantuml: command not found`. This was the definitive proof. Despite my `flake.nix` being correct, the *active terminal session I was in* was a stale environment, loaded *before* I had made the changes. It was like changing the blueprints for a house while still standing inside the old one. The fix was deceptively simple but profoundly important in the world of Nix: ```bash # Exit the old, stale shell (if in one) exit # Reload the environment from the updated flake.nix nix develop ``` Upon re-entering the shell, `which plantuml` immediately returned the correct path in the Nix store. ## The Payoff: Art in the Machine ๐ŸŽจ ----- ## The Payoff: Art in the Machine ๐ŸŽจ With the environment finally correct, the last hurdle was the script's own logic. The initial regex-based parser for the `.dot` file was too brittle and failed to extract the class data, producing an empty diagram. We switched to the `pydot` libraryโ€”a proper tool for the jobโ€”and after one last round of polishing the string-cleaning logic, we ran `prompt_foo.py` one final time. Success. The XML context was now perfectly formed, containing a beautiful, clean ASCII art UML diagram right inside the `` tag. The machine now had its x-ray vision. The patient is prepped, the tools are sterilized, and the AI is ready. Now, we can finally begin the amputation. ```plaintext Below is a UML class diagram for server.py: โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚Chat โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚DictLikeDB โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚- active_chat_tasks โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚OrderedMessageQueue โ”‚ โ”‚- active_websockets โ”‚ โ”‚- Store โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚- app โ”‚ โ”‚- store โ”‚ โ”‚- _current_step โ”‚ โ”‚- first_connection_handled โ”‚ โ”‚+ __contains__(key) โ”‚ โ”‚- _processing โ”‚ โ”‚- id_suffix โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚+ __delitem__(key) โ”‚ โ”‚- _step_complete โ”‚ โ”‚- last_message โ”‚ โ”‚DOMSkeletonMiddleware โ”‚ โ”‚+ __getitem__(key) โ”‚ โ”‚- _step_started โ”‚ โ”‚- last_message_time โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚+ __init__(store, Store) โ”‚ โ”‚- _workflow_context โ”‚ โ”‚- logger โ”‚ โ”‚+ dispatch(request, call_next)
``` --- **Me**: > And here I cut this article. That's enough, isn't it? Pshwew! Prep the git > repo patient now. Amputate cruft later. But if you do the Prompt Foo process > and view that output, boy is it sweet! Hope the AIs think the same thing. --- ## Book Analysis ### Ai Editorial Take This is a premium technical blog post. It's not just a 'how-to'; it's a 'how-we-did-it-and-why-it-was-hard.' The narrative structure makes it far more engaging than a simple tutorial. The core value lies in its detailed illustration of a non-trivial debugging process within a modern, complex stack (Nix + Python). This is precisely the kind of deep, experience-based content that resonates with senior developers and engineers. It has strong potential to be a cornerstone piece in a book about advanced DevOps or AI-assisted software engineering practices. ### Title Brainstorm * **Title Option:** Arming AI with Architectural X-Rays for Code Pruning * **Filename:** `ai-architectural-xrays-code-pruning.md` * **Rationale:** Directly states the core purpose and benefit. 'Architectural X-Rays' is a strong metaphor for the UML/DOT diagrams, and 'Code Pruning' is the end goal. Highly descriptive and SEO-friendly. * **Title Option:** The Stale Shell: Debugging a Nix and Python Toolchain * **Filename:** `debugging-nix-python-stale-shell.md` * **Rationale:** Focuses on the central 'aha!' moment of the debugging process. 'Stale Shell' is a memorable and relatable problem for anyone who has worked with complex environments. * **Title Option:** From 'Command Not Found' to ASCII Art: An AI Workflow Story * **Filename:** `command-not-found-to-ascii-art.md` * **Rationale:** Tells the story of the journey from a common, frustrating error to the final, successful and unique output. It's a narrative title that captures the reader's interest. ### Content Potential And Polish - **Core Strengths:** - Authentic Problem-Solving Narrative: The article tells a compelling, real-world story of debugging, which is highly relatable to a technical audience. - Clear Technical Explanation: It masterfully explains the subtle but critical difference between managing dependencies in `flake.nix` versus `requirements.txt`. - Strong Metaphors: The use of analogies like 'workshop vs. toolbox' and 'architectural x-rays' makes complex concepts accessible and memorable. - **Suggestions For Polish:** - Explicitly state the final, working `pydot` solution. The article mentions switching from regex to `pydot`, but showing the final, robust Python code block that solved the parsing would provide immense value. - Add a concluding paragraph that reflects on the broader implications of this workflow, perhaps touching on how this level of context-engineering is the future of human-AI collaboration in software development. - Consider embedding a small, final example of the successful ASCII art directly in the article to provide a visual payoff for the reader. ### Next Step Prompts - You are a DevOps engineer. Based on the successful creation of the automated context generator in the provided article, write a new Python script that consumes the final XML output, parses the 'pruning analysis' from the AI's response, and stages `git rm` commands for the files identified as 'High Confidence' orphans for manual review. - Write a new section for the article titled 'Beyond Code: Finding Orphaned Assets.' Using the context provided, detail a strategy using `ripgrep` and Python scripting to cross-reference the list of SVG files in `assets/feather/` against their usage in the entire codebase (Python files, JS, HTML) to identify unused icons.