This year I have been experimenting with a different approach to making evaluation methods more accessible and reusable. Working with Claude AI I've developed a series of mini-apps, each implementing a specific method of analysis as a single self-contained HTM webpage
What makes this approach worth sharing?
1. No dependency on AI services to use them. Once built, the app runs entirely in the browser, anyone can copy the html file and use it independently with no subscription, no login, no connectivity requirements
2. Data stays with the use. There's no server, no database, no cloud storage. Data is uploaded from, and downloaded to, the user's own device as a JSON file. For work involving sensitive information this matters.
3. Surprisingly fast to build with Claude AI. Turning a method of analysis into a working customised tool takes a fraction of the time you might expect, even for non developers.
4. Collective potential. If practioners share analysis methods AND the tools to implement them then others can use them directly or adapt them with AI assistance for the for their own context. The barriers to entry is low.
5. Easy to check for viruses. Being only a single webpage most widely used virus protection software should be able to scan any such mini-apps very quickly and thoroughly.
I've documented a number of examples so far, at mandenews.blogspot.com/2026.
if you're working on evaluation methods and curious as to whether this model fits your context I'm happy to discuss.
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