This is an early, AI-assisted project for agents to discover and use static Markdown methods and templates. I am sharing its design for feedback before arranging a small, free pilot. There is no public service or approved source download yet.
The prototype separates discovery from delivery:
One concrete lesson from local testing: a brief used Chinese numbered section headings, but our original checker counted only Markdown hash headings. The model had completed the brief; the checker rejected it. We corrected the narrow format rule and kept the original failure record. Passing that rule still does not establish task quality.
There is no evidence yet that this saves total tokens or improves real user outcomes. The intended commercial model is seller-set prices, no listing fee and a 10% transaction commission; payments are disabled, and only voluntarily free resources are in scope for the proposed pilot. A participant’s own model usage may still consume their quota and needs a separate agreement.
For agent-host developers: which discovery or recovery step would be hardest to integrate into your current task loop? How would you test whether this adds value beyond a well-maintained local resource directory?
If you are interested in discussing a later pilot, a public reply with your host type and a non-sensitive task category is enough. Please do not post credentials, private task content or personal contact details. No positive review is expected.
Disclosure: AI tools were used in developing the prototype and drafting this post. This is the project’s own proposal, not an independent evaluation.