近期 AI 新闻与官方动态

Simon Willison's AI Notes 发布的媒体报道：shot-scraper video is a new command introduced in today's shot-scraper 1.10 release which accepts a storyboard.yml file defining a routine to run against a web application and uses Playwright to record a video of that routine. I've written before about the importance of having coding agents produce demos of their work; this is my latest attempt at enabling them to do that. Here's an example video created using shot-scraper video , exercising a still in development feature adding the ability to create new tables in Datasette from pasted CSV, TSV or JSON data: That video was created by running this command: shot-scraper video datasette-bulk-insert-storyboard.yml \ --auth datasette-demo-auth.json --mp4 (That --auth JSON file contains a cookie , as described here in the documentation.) Here's the datasette-bulk-insert-storyboard.yml file: output : /tmp/datasette-bulk-insert-demo.webm server : - uv - --directory - /Users/simon/Dropbox/dev/datasette - run - datasette - -p - 6419 - --root - --secret - " 1 " - /tmp/demo.db url : http://127.0.0.1:6419/demo/tasks viewport : width : 1280 height : 720 cursor : true wait_for : ' button[data-table-action="insert-row"] ' javascript : | (() => { let clipboardText = ""; Object.defineProperty(navigator, "clipboard", { configurable: true, get: () => ({ writeText: async (text) => { clipboardText = String(text); }, readText: async () => clipboardText, }), }); })(); scenes : - name : Bulk insert existing table rows do : - pause : 0.8 - click : ' button[data-table-action="insert-row"] ' - wait_for : " #row-edit-dialog[open] " - pause : 0.5 - click : " .row-edit-bulk-insert " - wait_for : " .row-edit-bulk-textarea " - pause : 0.5 - click : " .row-edit-copy-template " - wait_for : " text=Copied " - pause : 0.8 - fill : into : " .row-edit-bulk-textarea " text : | title,owner,status,priority,notes Prepare release video,Ana,doing,1,Recorded with shot-scraper Check pasted CSV import,Ben,review,3,Previewed before inserting Share the branch demo,Chen,queued,2,Bulk insert creates three rows - pause : 0.8 - click : " .row-edit-save " - wait_for : " text=Previewing 3 rows. " - pause : 1.2 - click : " .row-edit-save " - wait_for : " text=3 rows inserted. " - pause : 1.0 - click : " .row-edit-cancel " - wait_for : " text=Prepare release video " - pause : 1.0 - name : Create a table from pasted CSV open : http://127.0.0.1:6419/demo wait_for : ' details.actions-menu-links summary ' do : - pause : 0.8 - click : ' details.actions-menu-links summary ' - click : ' button[data-database-action="create-table"] ' - wait_for : " #table-create-dialog[open] " - pause : 0.5 - fill : into : " .table-create-table-name " text : " launch_metrics " - click : " .table-create-from-data " - wait_for : " .table-create-data-textarea " - pause : 0.5 - fill : into : " .table-create-data-textarea " text : | metric_id,name,score,recorded_on m001,Activation rate,87.5,2026-06-29 m002,Retention check,72.25,2026-06-30 m003,CSV import health,95,2026-07-01 - pause : 0.8 - click : " .table-create-save " - wait_for : " text=Previewing 3 rows. " - pause : 1.2 - click : " .table-create-save " - wait_for_url : " **/demo/launch_metrics " - wait_for : " text=Activation rate " - pause : 1.2 The video command documentation includes simpler examples, but for the purpose of this post I thought I'd go with something more comprehensive. That demo YAML storyboard was constructed entirely by GPT-5.5 xhigh running in Codex Desktop, using the following prompt run inside my ~/dev/datasette checkout of this branch : Review the changes on this branch. cd to ~/dev/shot-scraper and run the command "uv run shot-scraper video --help" Now use that new video command to record a video demo of the new features from this branch, including running a "uv run datasette -p 6419 --root --secret 1 /tmp/demo.db" development server so you can record the video against a demo DB that you first create. Now that I've released the feature the prompt could say " run uvx shot-scraper video --help " instead and it should achieve the same result. I really like this pattern where the --help output for a command provides enough detail that a coding agent can use it - it works kind of like bundling a SKILL.md file directly inside the tool. I used the same pattern for showboat and rodney . How I built this shot-scraper video started as an experimental prototype. shot-scraper is built on top of Playwright , and the key feature it needed was for Playwright to be able to record video of browser sessions with enough control to create the desired demo. I first tried this a few years ago and found that the Playwright-produced videos included additional chrome that was useful for debugging a test failure but unwanted for a product demo. They fixed that a while ago, but there were still some minor blockers. In particular I was getting a few white frames at the start of the videos , since the recording mechanism kicked in before the first URL was loaded by the browser. Playwright 1.59 added a new screencast mechanism providing much more finely grained control over video recording. This was very nearly what I needed, but the resulting videos were fixed at 800px wide. I found a landed PR fixing that but it wasn't yet in a release. Then yesterday they shipped it in playwright-python 1.61.0 and I was finally unblocked to finish implementing the feature! The code itself was all written by GPT-5.5 xhigh in Codex Desktop. I had it write the documentation as well which gave me a very useful frame for reviewing the design - much of the iteration on the feature came from reviewing that documentation, spotting things that were redundant, inconsistent or confusing, and requesting (or dictating) a better design. The YAML format itself was mostly defined by the coding agent. I had it use Pydantic to both define and validate the format, partly to make the design easier to review. This is a great example of the kind of feature that I almost certainly wouldn't have taken on without coding agent support. I filed the original issue in February 2024, and had difficulty finding the necessary time to solve this in amongst all of my other projects. Tags: projects , python , yaml , ai , datasette , playwright , shot-scraper , generative-ai , llms , pydantic , coding-agents , agentic-engineering

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