An Embeddable SQLite Parser
424k statements/sec with zero dependencies — sqlparse can't match this performance.

Creative Commons for AI provenance, but execution is prototype-stage; needs engineering lift.
Content creators, platforms, educators, researchers, and journalists publishing mixed human-AI work
The idea: a declare-ai.json file that any creator, platform, or AI tool can publish alongside content — declaring what percentage was written, coded, illustrated, or researched by AI versus humans, which tools were used, and who the human contributors are. A lightweight embeddable widget displays it as a collapsible pie chart. A browser extension auto-detects it on any page. A community forum handles disputes.
Think Creative Commons, but for AI provenance. Or a nutrition label, but for intelligence.
The demo is a full interactive developer briefing — architecture diagram, JSON schema, forum mockup with a real dispute thread example, tech stack recommendation, and phased roadmap. The widget on the page declares itself.
I've gifted it as MIT. I'm looking for developers who want to own this with me.
GitHub: https://github.com/Declare-AI/declare-ai Live demo: https://declare-ai.github.io/declare-ai/declare-ai-devteam.h...
Genuinely open to all feedback — including "this already exists and here's why it won't work."
424k statements/sec with zero dependencies — sqlparse can't match this performance.
JSON-configured API flow testing CLI competing with Postman and k6.
Declarative schema mapping replaces cryptic awk $1 column indexing with named fields.
Verifiable floor of 0.29% AI code in the kernel using the new Assisted-by tag.
Schema-to-server codegen for MCP, but targets the crowded AI app layer.
Client-side ranking of 50k developers with zero backend—clever constraint engineering.