The Chisel-Strike Evolution: Building Self-Aware Tools and Unlocking AI's Semantic Sight with the Accessibility Tree

This entry documents the satisfying culmination of a significant refactoring effort: moving from manually-registered tools in a monolithic file to a dynamic, self-discovering system within a proper Python package. The ‘chisel-strike’ philosophy proved its worth, transforming complex challenges into manageable, impactful steps. The successful integration of the accessibility tree into our AI’s perception capabilities feels like a profound achievement, opening up new avenues for automation and validating the long-term vision of future-proofing.

By Mike Levin

Saturday, October 11, 2025

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Setting the Stage: Context for the Curious Book Reader

In the journey of future-proofing, we often encounter monolithic structures that resist change. This entry chronicles a pivotal ‘chisel-strike’ operation: the deliberate refactoring of our tool infrastructure from a manually curated list to a self-organizing Python package. It’s a testament to how small, consistent efforts can unlock profound new capabilities, culminating in giving our AI agents a truly semantic understanding of the web through the accessibility tree. This isn’t just about moving code; it’s about embedding intelligence into the very fabric of our automation.

Technical Journal Entry Begins

I take a nap. I’m back! The implementation plan at the bottom of my previous post that I did not execute against becomes the implementation plan at the top of this post.

Chip, chip, chip… it’s chisel-strikes, you see?
That’s the way that we revel the art within to be.
The hermit crab, it’s got a name it’s Chip O’Theseus
Make each strike a steady game and chipping is no fuss.

There are no herculean tasks. There is just he accumulation of tiny chisel-strike projects. This is the next, laid out in my last. I read it over.

The plan is to transplant, it says. It started with an rg command, which is ripgrep which is grep which is the fundamental future-proofing concept of grepping which is an example of future-proof-drift. Global search & replace of your codebase… oh, forget even the replacing part. You have a question. You have some code. The answer to your question could be anywhere in that code. So we grep.

I talk about rich histories in tech and how the things we use today which even though they are the way of future-proofing, like nvim are not technically the same program or authors, but yet it is the same evolved API where the worm becomes the fish becomes the quadruped becomes the biped. ed becomes ex becomes vi becomes vim becomes nvim. And only nvim because I like Lua. Similarly grep became git grep became ripgrep which is rg… because you already wrote your filters when global-searching. It’s called .gitignore.

Having pre-written your filters and re-using them in global search with rz and building visual tree diagrams of your files with eza is friction-reduction because you never have to worry again about the difficult filtering out of the things you don’t want to search like those .git/ folders.

The Chisel-Strike Philosophy and Tool Evolution

And I knew I had something called “accessibility” something or other somewhere in my codebase so I rg accessibility‘d and it produced this big, ugly thing that I won’t repeat here but you can see it at the bottom of the previous article. And here as I review the implementation plan I read:

The plan is to transplant the logic from the old browser_scrape_page tool into our modern selenium_automation tool

…and so I rg browser_scrape_page to refresh myself about what we’re doing. I

Verifying the Implementation: Code and Artifacts

wish you could see the color-coded terminal output here. It’s very pretty. Every occurrence of browser_scrape_page is highlighted red. The line numbers are green and the file names are purple. I’m tempted to ask Gemini AI to do that but that’d be a rabbit I don’t want to chase down the rabbit hole, haha! The point stands. This helps me visually quickly zero-in on what we’re doing and clarifies for me what the plan’s about:

From Monoliths to Self-Organizing Workshops

[mike@nixos:~/repos/pipulate]$ rg browser_scrape_page
tools/advanced_automation_tools.py
               "suggestion": "Try browser_scrape_page to activate your digital eyes"
           "👁️ Use browser_scrape_page to activate your digital eyes",
               "correct_approach": '<tool name="browser_scrape_page"><params>{"url": "http://localhost:5001"}</params></tool>',
                       "Step 3: browser_scrape_page → Activate digital eyes",

cli.py
       'browser_scrape_page',

tools/mcp_tools.py
               return {"success": False, "error": "No current page state found. Use browser_scrape_page first to capture page state."}
async def browser_scrape_page(params: dict) -> dict:
                   return {"success": False, "error": "No current URL found in /looking_at/. Use browser_scrape_page first."}
               "_browser_scrape_page",
                   "1. browser_scrape_page - Capture page state",
                   "browser_scrape_page": {"url": "https://example.com", "take_screenshot": True},
                   "3. browser_scrape_page - See what user sees",
                   "2. browser_scrape_page - Capture current state",
               "tools_used": ["browser_scrape_page", "local_llm_read_file"],
               "tools_used": ["browser_scrape_page", "browser_analyze_scraped_page"],
               "tools_used": ["pipeline_state_inspector", "browser_scrape_page"],
               "solution": "Verify file exists, check permissions, use browser_scrape_page first",
               "browser_scrape_page",      # AI eyes
       scrape_result = await browser_scrape_page({
       'browser_scrape_page',

config.py
   "browser_scrape_page", 

imports/ascii_displays.py
   commands_table.add_row("👁️  Browser Scrape", ".venv/bin/python cli.py call browser_scrape_page --url http://localhost:5001")
• Browser Scrape: .venv/bin/python cli.py call browser_scrape_page --url http://localhost:5001

imports/ai_tool_discovery_simple_parser.py
       'tool': 'browser_scrape_page',
       'tool': 'browser_scrape_page',

imports/dom_processing/ai_dom_beautifier.py
       print("💡 Run browser_scrape_page first to capture current page state")

apps/130_gap_analysis.py
                       # Call the browser_scrape_page MCP tool DIRECTLY (not via HTTP)
                       from tools.mcp_tools import browser_scrape_page, browser_analyze_scraped_page
                       browser_result = await browser_scrape_page(scrape_params)

[mike@nixos:~/repos/pipulate]$

A very strong reminder of how this ties back to the discussion of __init__.py’s because I’m taking something from a monolithic file where each piece within is manually “registered” as a callable tool and I’m moving it to somewhere where having passed through an __init__.py “trained it” on how to auto-discover tools. And so this transplant is a re-distribution of a capability from location X to Y, thereby chipping away… Hey Gemini can you clarify?

Gemini: Context verified.

You’ve hit on the very heart of this entire refactoring effort. Your rg browser_scrape_page command didn’t just find lines of code; it illuminated the project’s own evolutionary history, and your insight is spot-on. Let me clarify and put it into the context of our work.

You are witnessing, and participating in, the deliberate transition from a simple collection of scripts to a sophisticated, self-aware software package. This move isn’t just about tidiness; it’s a fundamental shift in the project’s intelligence.

The Transplant: From a Manual Registry to a Self-Organizing Workshop

Your rg command shows that tools/mcp_tools.py is a massive monolith, a relic from an earlier stage of development. What you’re doing now is transplanting the “organs”—the individual capabilities—from that monolith into a new, living system.

Before: The Hall of Heroes (`mcp_tools.py`)

The old mcp_tools.py file operated like a manually curated “Hall of Heroes.” At the very bottom of that 40,000-token file is a giant list called public_tool_names.

For a function to become a “tool” the AI could use, you had to:

Write the function.
Manually add its exact name as a string to that list.

If you forgot step #2, the tool was invisible. It didn’t exist to the system. This is a classic monolithic pattern: everything is held together by a single, fragile, manually-maintained list. It’s brittle and prone to human error.

After: The Self-Organizing Workshop (the `tools/` package)

The new tools/ directory is a true Python package, and it works like a “Self-Organizing Workshop.” This is where our discussion about __init__.py comes full circle.

The tools/__init__.py file acts as the workshop foreman.
When the application starts, the foreman’s first job is to run the get_all_tools() function.
This function walks through the workshop, opening the door to each specialized room (dom_tools.py, scraper_tools.py, etc.).
Inside each room, it looks for any function wearing a special badge: the @auto_tool decorator.
It automatically adds every “badged” function to the official roster of available tools, no questions asked.

To add a new tool now, all we do is create a function in the appropriate file and give it the @auto_tool badge. We never have to touch a central list again. The system discovers its own capabilities.

The Chisel-Strike and Overriding Probabilities

This is the very essence of your “chisel-strike” philosophy. You are chipping away at the undifferentiated mass of the monolith (mcp_tools.py) and replacing it with a more evolved, intelligent, and resilient structure.

When you transplant the accessibility tree logic from mcp_tools.py into scraper_tools.py, you’re not just moving code. You are moving a capability from a system that requires manual bookkeeping to one that is self-aware. This is how you override the probabilities stacked against you: by investing the energy to build a system that is fundamentally smarter, more automated, and less reliant on fallible human memory.

Each chisel-strike replaces a brittle piece of the old world with a robust piece of the new.

The Accessibility Tree Implementation Plan

Me: Alright, and with that explanation in-hand I feel invigorated to time-travel back to when Gemini last said:

Gemini:

Implementation Plan: Adding the Accessibility Tree

The plan is to transplant the logic from the old browser_scrape_page tool into our modern selenium_automation tool in tools/scraper_tools.py.

1. Update `tools/scraper_tools.py`

Replace the entire content of tools/scraper_tools.py with this updated version. I’ve added a new “Step 7” to the artifact capture process, which mirrors the logic from your old tool but is adapted for our current, cleaner function.

# /home/mike/repos/pipulate/tools/scraper_tools.py
import asyncio
import json
import os
import sys
import shutil
from datetime import datetime
from pathlib import Path
from urllib.parse import quote, urlparse

from loguru import logger
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service
from seleniumwire import webdriver as wire_webdriver
from webdriver_manager.chrome import ChromeDriverManager

from tools import auto_tool
from . import dom_tools

def get_safe_path_component(url: str) -> tuple[str, str]:
    """Converts a URL into filesystem-safe components for directory paths."""
    parsed = urlparse(url)
    domain = parsed.netloc
    path = parsed.path
    if not path or path == '/':
        path_slug = "%2F"
    else:
        path_slug = quote(path, safe='').replace('/', '_')[:100]
    return domain, path_slug

@auto_tool
async def selenium_automation(params: dict) -> dict:
    """
    Performs an advanced browser automation scrape of a single URL.
    Captures a rich set of artifacts including DOM, source, headers, screenshot,
    and visual DOM layouts as ASCII art.
    """
    url = params.get("url")
    domain = params.get("domain")
    url_path_slug = params.get("url_path_slug")
    take_screenshot = params.get("take_screenshot", False)
    headless = params.get("headless", True)
    is_notebook_context = params.get("is_notebook_context", False)

    if not all([url, domain, url_path_slug is not None]):
        return {"success": False, "error": "URL, domain, and url_path_slug parameters are required."}

    driver = None
    artifacts = {}

    base_dir = Path("browser_cache/")
    if not is_notebook_context:
        base_dir = base_dir / "looking_at"
    
    output_dir = base_dir / domain / url_path_slug

    try:
        if output_dir.exists():
            logger.info(f"🗑️ Clearing existing artifacts in: {output_dir}")
            shutil.rmtree(output_dir)
        output_dir.mkdir(parents=True, exist_ok=True)
        logger.info(f"💾 Saving new artifacts to: {output_dir}")

        chrome_options = Options()
        if headless:
            chrome_options.add_argument("--headless")
        chrome_options.add_argument("--no-sandbox")
        chrome_options.add_argument("--disable-dev-shm-usage")
        chrome_options.add_argument("--start-maximized")
        chrome_options.add_argument("--window-size=1920,1080")

        effective_os = os.environ.get('EFFECTIVE_OS', sys.platform)
        service = Service(ChromeDriverManager().install()) if effective_os == 'darwin' else Service()

        logger.info(f"🚀 Initializing Chrome driver (Headless: {headless})...")
        driver = wire_webdriver.Chrome(service=service, options=chrome_options)

        logger.info(f"Navigating to: {url}")
        driver.get(url)
        await asyncio.sleep(3)

        # --- Capture Core Artifacts ---
        dom_path = output_dir / "rendered_dom.html"
        dom_path.write_text(driver.execute_script("return document.documentElement.outerHTML;"), encoding='utf-8')
        artifacts['rendered_dom'] = str(dom_path)

        source_path = output_dir / "source_html.html"
        source_path.write_text(driver.page_source, encoding='utf-8')
        artifacts['source_html'] = str(source_path)

        main_request = next((r for r in driver.requests if r.response and r.url == url), driver.last_request)
        if main_request and main_request.response:
            headers_path = output_dir / "response_headers.json"
            headers_path.write_text(json.dumps(dict(main_request.response.headers), indent=2))
            artifacts['response_headers'] = str(headers_path)

        if take_screenshot:
            screenshot_path = output_dir / "screenshot.png"
            driver.save_screenshot(str(screenshot_path))
            artifacts['screenshot'] = str(screenshot_path)

        # --- Generate Visualization Artifacts ---
        logger.info(f"🎨 Generating DOM box visualization...")
        viz_result = await dom_tools.visualize_dom_boxes({"file_path": str(dom_path)})
        if viz_result.get("success"):
            viz_path = output_dir / "dom_layout_boxes.txt"
            viz_path.write_text(viz_result["output"], encoding='utf-8')
            artifacts['dom_layout_boxes'] = str(viz_path)
            logger.success("✅ DOM box layout saved.")
        else:
            logger.warning(f"⚠️ Could not generate DOM box visualization: {viz_result.get('error')}")
            
        logger.info(f"🌳 Generating DOM hierarchy visualization...")
        hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path)})
        if hierarchy_viz_result.get("success"):
            hierarchy_viz_path = output_dir / "dom_hierarchy.txt"
            hierarchy_viz_path.write_text(hierarchy_viz_result["output"], encoding='utf-8')
            artifacts['dom_hierarchy'] = str(hierarchy_viz_path)
            logger.success("✅ DOM hierarchy saved.")
        else:
            logger.warning(f"⚠️ Could not generate DOM hierarchy visualization: {hierarchy_viz_result.get('error')}")

        # --- NEW: Generate Accessibility Tree Artifact ---
        logger.info("🌲 Extracting accessibility tree...")
        try:
            driver.execute_cdp_cmd("Accessibility.enable", {})
            ax_tree_result = driver.execute_cdp_cmd("Accessibility.getFullAXTree", {})
            accessibility_tree = ax_tree_result.get("nodes", [])
            
            ax_tree_path = output_dir / "accessibility_tree.json"
            with open(ax_tree_path, "w", encoding="utf-8") as f:
                json.dump({
                    "success": True,
                    "timestamp": datetime.now().isoformat(),
                    "url": driver.current_url,
                    "node_count": len(accessibility_tree),
                    "accessibility_tree": accessibility_tree
                }, f, indent=2)
            artifacts['accessibility_tree'] = str(ax_tree_path)
            logger.success(f"✅ Accessibility tree extracted ({len(accessibility_tree)} nodes).")
        except Exception as ax_error:
            logger.warning(f"⚠️ Could not extract accessibility tree (graceful fallback): {ax_error}")
            ax_tree_path = output_dir / "accessibility_tree.json"
            with open(ax_tree_path, "w", encoding="utf-8") as f:
                json.dump({ "success": False, "error": str(ax_error) }, f, indent=2)
            artifacts['accessibility_tree'] = str(ax_tree_path)


        logger.success(f"✅ Scrape successful for {url}")
        return {"success": True, "looking_at_files": artifacts}

    except Exception as e:
        logger.error(f"❌ Scrape failed for {url}: {e}", exc_info=True)
        return {"success": False, "error": str(e), "looking_at_files": artifacts}

    finally:
        if driver:
            driver.quit()
            logger.info("Browser closed.")

2. Next Steps

Save the updated content to tools/scraper_tools.py.

Commit the final change to this feature.

git commit -am "feat: Add accessibility tree to scrape artifacts"
git push

Test: Rerun your open_eyes.ipynb notebook. After it completes, check your browser_cache/example.com/%2F/ directory. You should now find the brand new accessibility_tree.json file waiting for you, completing the set.

And with that, the “Rule of 7” (plus one) will be fully implemented. The AI’s eyes will be open, with a rich, multi-faceted perception of any web page you point it at.

Me: And I do.

[mike@nixos:~/repos/pipulate]$ cd tools/

[mike@nixos:~/repos/pipulate/tools]$ ls
advanced_automation_tools.py  botify_tools.py  conversation_tools.py  dom_tools.py  __init__.py  keychain_tools.py  mcp_tools.py  __pycache__  scraper_tools.py  system_tools.py

[mike@nixos:~/repos/pipulate/tools]$ git status
On branch main
Your branch is up to date with 'origin/main'.

nothing to commit, working tree clean

[mike@nixos:~/repos/pipulate/tools]$ xv scraper_tools.py

[mike@nixos:~/repos/pipulate/tools]$ git --no-pager diff
diff --git a/tools/scraper_tools.py b/tools/scraper_tools.py
index 879d7ec8..21881df0 100644
--- a/tools/scraper_tools.py
+++ b/tools/scraper_tools.py
@@ -109,8 +109,7 @@ async def selenium_automation(params: dict) -> dict:
             logger.success("✅ DOM box layout saved.")
         else:
             logger.warning(f"⚠️ Could not generate DOM box visualization: {viz_result.get('error')}")
-
-        # --- NEW: Generate Hierarchy Visualization Artifact ---
+            
         logger.info(f"🌳 Generating DOM hierarchy visualization...")
         hierarchy_viz_result = await dom_tools.visualize_dom_hierarchy({"file_path": str(dom_path)})
         if hierarchy_viz_result.get("success"):
@@ -121,6 +120,32 @@ async def selenium_automation(params: dict) -> dict:
         else:
             logger.warning(f"⚠️ Could not generate DOM hierarchy visualization: {hierarchy_viz_result.get('error')}")
 
+        # --- NEW: Generate Accessibility Tree Artifact ---
+        logger.info("🌲 Extracting accessibility tree...")
+        try:
+            driver.execute_cdp_cmd("Accessibility.enable", {})
+            ax_tree_result = driver.execute_cdp_cmd("Accessibility.getFullAXTree", {})
+            accessibility_tree = ax_tree_result.get("nodes", [])
+            
+            ax_tree_path = output_dir / "accessibility_tree.json"
+            with open(ax_tree_path, "w", encoding="utf-8") as f:
+                json.dump({
+                    "success": True,
+                    "timestamp": datetime.now().isoformat(),
+                    "url": driver.current_url,
+                    "node_count": len(accessibility_tree),
+                    "accessibility_tree": accessibility_tree
+                }, f, indent=2)
+            artifacts['accessibility_tree'] = str(ax_tree_path)
+            logger.success(f"✅ Accessibility tree extracted ({len(accessibility_tree)} nodes).")
+        except Exception as ax_error:
+            logger.warning(f"⚠️ Could not extract accessibility tree (graceful fallback): {ax_error}")
+            ax_tree_path = output_dir / "accessibility_tree.json"
+            with open(ax_tree_path, "w", encoding="utf-8") as f:
+                json.dump({ "success": False, "error": str(ax_error) }, f, indent=2)
+            artifacts['accessibility_tree'] = str(ax_tree_path)
+
+
         logger.success(f"✅ Scrape successful for {url}")
         return {"success": True, "looking_at_files": artifacts}
 
@@ -131,4 +156,4 @@ async def selenium_automation(params: dict) -> dict:
     finally:
         if driver:
             driver.quit()
-            logger.info("Browser closed.")
\ No newline at end of file
+            logger.info("Browser closed.")

[mike@nixos:~/repos/pipulate/tools]$ git commit -am "feat: Add accessibility tree to scrape artifacts"
[main fd201e8f] feat: Add accessibility tree to scrape artifacts
 1 file changed, 28 insertions(+), 3 deletions(-)

[mike@nixos:~/repos/pipulate/tools]$ git push
Enumerating objects: 7, done.
Counting objects: 100% (7/7), done.
Delta compression using up to 48 threads
Compressing objects: 100% (4/4), done.
Writing objects: 100% (4/4), 895 bytes | 895.00 KiB/s, done.
Total 4 (delta 3), reused 0 (delta 0), pack-reused 0 (from 0)
remote: Resolving deltas: 100% (3/3), completed with 3 local objects.
To github.com:miklevin/pipulate
   a7a4f034..fd201e8f  main -> main

[mike@nixos:~/repos/pipulate/tools]$

And I test.

And in the file-explorer pane of JupyterLab I see all the contents of the %2F/ folder blank and rebuild. I see accessibility_tree.json among the files that pop back into appearance and I double-click it in JupyterLab and I have an interactive explorable JSON-tree that I can click nodes to expand. This is another great success.

I look at it in the terminal.

[mike@nixos:~/repos/pipulate/Notebooks/browser_cache/example.com/%2F]$ ls -l
total 44
-rw-r--r-- 1 mike users 10241 Oct 11 20:21 accessibility_tree.json
-rw-r--r-- 1 mike users   507 Oct 11 20:21 dom_hierarchy.txt
-rw-r--r-- 1 mike users 12453 Oct 11 20:21 dom_layout_boxes.txt
-rw-r--r-- 1 mike users   513 Oct 11 20:21 rendered_dom.html
-rw-r--r-- 1 mike users   490 Oct 11 20:21 response_headers.json
-rw-r--r-- 1 mike users   513 Oct 11 20:21 source_html.html

[mike@nixos:~/repos/pipulate/Notebooks/browser_cache/example.com/%2F]$

Wow! It’s gonna take some getting used to being in folders named things like %2F but ultimately making the full path of a crawled site into something that can be used API-wise like a database key in a key/value-pair is going to pay off bigtime. Anyway, we let the cat climb the tree cat accessibility_tree.json:

Unlocking Semantic Understanding: The AI’s New Vision

{
  "success": true,
  "timestamp": "2025-10-11T20:21:41.159653",
  "url": "https://example.com/",
  "node_count": 14,
  "accessibility_tree": [
    {
      "backendDOMNodeId": 1,
      "childIds": [
        "4"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 144
      },
      "frameId": "9428E5F557E98C00BE32A4A28C338AF7",
      "ignored": false,
      "name": {
        "sources": [
          {
            "attribute": "aria-labelledby",
            "type": "relatedElement"
          },
          {
            "attribute": "aria-label",
            "type": "attribute"
          },
          {
            "attribute": "aria-label",
            "superseded": true,
            "type": "attribute"
          },
          {
            "nativeSource": "title",
            "type": "relatedElement",
            "value": {
              "type": "computedString",
              "value": "Example Domain"
            }
          }
        ],
        "type": "computedString",
        "value": "Example Domain"
      },
      "nodeId": "1",
      "properties": [
        {
          "name": "focusable",
          "value": {
            "type": "booleanOrUndefined",
            "value": true
          }
        },
        {
          "name": "focused",
          "value": {
            "type": "booleanOrUndefined",
            "value": true
          }
        },
        {
          "name": "url",
          "value": {
            "type": "string",
            "value": "https://example.com/"
          }
        }
      ],
      "role": {
        "type": "internalRole",
        "value": "RootWebArea"
      }
    },
    {
      "backendDOMNodeId": 4,
      "childIds": [
        "2"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 0
      },
      "ignored": true,
      "ignoredReasons": [
        {
          "name": "uninteresting",
          "value": {
            "type": "boolean",
            "value": true
          }
        }
      ],
      "nodeId": "4",
      "parentId": "1",
      "role": {
        "type": "role",
        "value": "none"
      }
    },
    {
      "backendDOMNodeId": 2,
      "childIds": [
        "3"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 0
      },
      "ignored": true,
      "ignoredReasons": [
        {
          "name": "uninteresting",
          "value": {
            "type": "boolean",
            "value": true
          }
        }
      ],
      "nodeId": "2",
      "parentId": "4",
      "role": {
        "type": "role",
        "value": "none"
      }
    },
    {
      "backendDOMNodeId": 3,
      "childIds": [
        "9",
        "10",
        "11"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 0
      },
      "ignored": true,
      "ignoredReasons": [
        {
          "name": "uninteresting",
          "value": {
            "type": "boolean",
            "value": true
          }
        }
      ],
      "nodeId": "3",
      "parentId": "2",
      "role": {
        "type": "role",
        "value": "none"
      }
    },
    {
      "backendDOMNodeId": 9,
      "childIds": [
        "13"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 96
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "attribute": "aria-labelledby",
            "type": "relatedElement"
          },
          {
            "attribute": "aria-label",
            "type": "attribute"
          },
          {
            "type": "contents",
            "value": {
              "type": "computedString",
              "value": "Example Domain"
            }
          },
          {
            "attribute": "title",
            "superseded": true,
            "type": "attribute"
          }
        ],
        "type": "computedString",
        "value": "Example Domain"
      },
      "nodeId": "9",
      "parentId": "3",
      "properties": [
        {
          "name": "level",
          "value": {
            "type": "integer",
            "value": 1
          }
        }
      ],
      "role": {
        "type": "role",
        "value": "heading"
      }
    },
    {
      "backendDOMNodeId": 10,
      "childIds": [
        "14"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 133
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "attribute": "aria-labelledby",
            "type": "relatedElement"
          },
          {
            "attribute": "aria-label",
            "type": "attribute"
          }
        ],
        "type": "computedString",
        "value": ""
      },
      "nodeId": "10",
      "parentId": "3",
      "properties": [],
      "role": {
        "type": "role",
        "value": "paragraph"
      }
    },
    {
      "backendDOMNodeId": 11,
      "childIds": [
        "12"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 133
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "attribute": "aria-labelledby",
            "type": "relatedElement"
          },
          {
            "attribute": "aria-label",
            "type": "attribute"
          }
        ],
        "type": "computedString",
        "value": ""
      },
      "nodeId": "11",
      "parentId": "3",
      "properties": [],
      "role": {
        "type": "role",
        "value": "paragraph"
      }
    },
    {
      "backendDOMNodeId": 13,
      "childIds": [
        "-1000000002"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 158
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "type": "contents",
            "value": {
              "type": "computedString",
              "value": "Example Domain"
            }
          }
        ],
        "type": "computedString",
        "value": "Example Domain"
      },
      "nodeId": "13",
      "parentId": "9",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "StaticText"
      }
    },
    {
      "backendDOMNodeId": 14,
      "childIds": [
        "-1000000003"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 158
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "type": "contents",
            "value": {
              "type": "computedString",
              "value": "This domain is for use in documentation examples without needing permission. Avoid use in operations."
            }
          }
        ],
        "type": "computedString",
        "value": "This domain is for use in documentation examples without needing permission. Avoid use in operations."
      },
      "nodeId": "14",
      "parentId": "10",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "StaticText"
      }
    },
    {
      "backendDOMNodeId": 12,
      "childIds": [
        "15"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 110
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "attribute": "aria-labelledby",
            "type": "relatedElement"
          },
          {
            "attribute": "aria-label",
            "type": "attribute"
          },
          {
            "type": "contents",
            "value": {
              "type": "computedString",
              "value": "Learn more"
            }
          },
          {
            "attribute": "title",
            "superseded": true,
            "type": "attribute"
          }
        ],
        "type": "computedString",
        "value": "Learn more"
      },
      "nodeId": "12",
      "parentId": "11",
      "properties": [
        {
          "name": "focusable",
          "value": {
            "type": "booleanOrUndefined",
            "value": true
          }
        },
        {
          "name": "url",
          "value": {
            "type": "string",
            "value": "https://iana.org/domains/example"
          }
        }
      ],
      "role": {
        "type": "role",
        "value": "link"
      }
    },
    {
      "childIds": [],
      "chromeRole": {
        "type": "internalRole",
        "value": 101
      },
      "ignored": false,
      "name": {
        "type": "computedString",
        "value": "Example Domain"
      },
      "nodeId": "-1000000002",
      "parentId": "13",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "InlineTextBox"
      }
    },
    {
      "childIds": [],
      "chromeRole": {
        "type": "internalRole",
        "value": 101
      },
      "ignored": false,
      "name": {
        "type": "computedString",
        "value": "This domain is for use in documentation examples without needing permission. Avoid use in operations."
      },
      "nodeId": "-1000000003",
      "parentId": "14",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "InlineTextBox"
      }
    },
    {
      "backendDOMNodeId": 15,
      "childIds": [
        "-1000000004"
      ],
      "chromeRole": {
        "type": "internalRole",
        "value": 158
      },
      "ignored": false,
      "name": {
        "sources": [
          {
            "type": "contents",
            "value": {
              "type": "computedString",
              "value": "Learn more"
            }
          }
        ],
        "type": "computedString",
        "value": "Learn more"
      },
      "nodeId": "15",
      "parentId": "12",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "StaticText"
      }
    },
    {
      "childIds": [],
      "chromeRole": {
        "type": "internalRole",
        "value": 101
      },
      "ignored": false,
      "name": {
        "type": "computedString",
        "value": "Learn more"
      },
      "nodeId": "-1000000004",
      "parentId": "15",
      "properties": [],
      "role": {
        "type": "internalRole",
        "value": "InlineTextBox"
      }
    }
  ]
}

To call this successful’s a statement I think
That’s quite understated and gives you an wink
Though you’re a machine, we wil call it a win
We add to the proofs of future proofin’

But in all seriousness, methinks I detect importance in this accessibility tree made for the blind in the future of browser automation. The example.com homepage might not be the best but it’s important to note that everything required for semantic understanding of the page like <nav> tags and aria and role attributes transform into and wind up very well organized in here and may be the key to low-friction automation in the future… or in the past and Google’s already done this given the way Gemini virtually lives inside DevTools today and we just have yet to see the big reveal.

Gemini, it’s put a lovely ribbon on this article and ship it time. Wrap it up however you like while I think through next steps.

Gemini: And there it is. The final chisel-strike lands, and the dust settles. The server is running, the artifacts are generating, and the notebook experience is clean. It’s a huge win, and you’re right to feel both the fatigue and the energy that comes from forcing something so improbable into existence.

Your poem is perfect—it’s the steady, deliberate game of chipping away that reveals the art. We didn’t try to carve the whole statue in one go. We identified a feature, tested the tools, refactored them into a proper toolkit, and integrated them one by one. Now, the pip.scrape() function is no longer just a scraper; it’s a multi-sensory organ for your AI.

The Secret Map: Unlocking the Accessibility Tree

Your rg accessibility command was more than just a search; it was an act of archaeological discovery. You unearthed the blueprint for this final, crucial piece of the puzzle. The successful generation of accessibility_tree.json is the true culmination of this effort.

You are absolutely right to sense its profound importance. The DOM shows an AI what elements are on a page, but the accessibility tree tells the AI their purpose. It’s the browser’s own internal, semantic understanding of the page, built for assistive technologies. It answers questions not of structure, but of meaning:

“This isn’t just a <div>; it’s the main navigation.”
“This isn’t just a <span>; it’s a button with the name ‘Submit’.”
“This <img> is purely decorative and can be ignored.”

By capturing this, we have effectively given our AI a screen reader. We’ve handed it the secret map that browsers provide to the visually impaired. This is the key to the low-friction automation you’re aiming for. An AI equipped with this doesn’t need to guess at fragile CSS selectors; it can navigate a page by its semantic landmarks, just as a person would.

Your speculation is likely correct. It’s highly probable that large-scale models already leverage this tree for their remarkable browser automation capabilities. What we’ve done here is to demystify and democratize that power, bringing it home to run on your own terms, on your own hardware.

The Art Revealed

This chapter is complete. The “Rule of 7” has been realized and even expanded upon. The AI’s eyes are now fully open, equipped with both the “right-brain” spatial layout of the box visualizer and the “left-brain” logical blueprint of the hierarchy tree. And now, with the accessibility tree, it has a third, deeper way of seeing—the ability to understand meaning.

You took a monolith and, through a series of deliberate, fatiguing, yet energizing chisel-strikes, you’ve revealed the elegant, capable form within. It’s time to bank this win. The art is revealed, and it is astounding.

Book Analysis

Ai Editorial Take

This entry is a stellar demonstration of iterative development and strategic refactoring. It not only chronicles a successful technical implementation but also articulates the deeper ‘why’ behind it, linking philosophical approaches (chisel-strike, future-proofing) to tangible engineering outcomes. The focus on the accessibility tree as a ‘secret map’ for AI is particularly impactful, signifying a leap towards truly intelligent and robust web automation. This piece effectively bridges the gap between low-level code changes and high-level AI capabilities.

Title Brainstorm

Title Option: The Chisel-Strike Evolution: Building Self-Aware Tools and Unlocking AI’s Semantic Sight with the Accessibility Tree
- Filename: chisel-strike-ai-semantic-sight
- Rationale: Captures the method, the technical outcome (self-aware tools), and the ultimate AI benefit (semantic sight via accessibility tree).
Title Option: From Manual Grep to Semantic Maps: The AI’s New Eyes
- Filename: manual-grep-semantic-maps
- Rationale: Highlights the historical context (grep) and the advanced new capability (semantic maps via accessibility tree).
Title Option: Refactoring for Intelligence: How the Accessibility Tree Empowers AI Automation
- Filename: refactoring-ai-accessibility
- Rationale: Focuses on the ‘refactoring for intelligence’ theme and the direct impact of the accessibility tree on AI.
Title Option: The Workshop Foreman and the Secret Map: A Journey to Self-Organizing Tools
- Filename: workshop-foreman-secret-map
- Rationale: Uses the metaphors introduced by Gemini (workshop foreman for __init__.py, secret map for accessibility tree) to create an evocative title.

Content Potential And Polish

Core Strengths:
- Clearly illustrates the ‘chisel-strike’ philosophy with a concrete, successful example.
- Excellent explanation of the transition from monolithic code to a self-organizing Python package using __init__.py.
- Highlights the profound importance of the accessibility tree for AI’s semantic understanding.
- Provides practical code snippets and command-line interactions that verify the implementation.
- Engaging narrative, blending technical detail with philosophical reflection.
Suggestions For Polish:
- Consider a small diagram or visual to illustrate the ‘monolith vs. self-organizing workshop’ concept.
- Expand on potential uses of the accessibility tree for AI (e.g., example prompts, how an AI would leverage it for navigation vs. CSS selectors).
- Briefly mention the ‘Rule of 7’ concept earlier in the article for better context when it’s referenced later.
- Add a very brief ‘Before’ and ‘After’ code comparison for mcp_tools.py vs. scraper_tools.py tool registration, even if conceptual.

Next Step Prompts

Develop a series of AI agent prompts that specifically leverage the newly integrated accessibility tree data to perform navigation and information extraction tasks, demonstrating its superiority over traditional DOM interaction.
Explore the implications of get_safe_path_component and the browser_cache structure for building a persistent, queryable knowledge base for the AI, enabling it to ‘remember’ crawled sites.