Feature: Difficulty rating system and ATP benchmarking attributes (@[difficulty])

I’d like to propose adding a metadata layer to the conjectures via a new @[difficulty] attribute. While the repository has excellent categorization, there isn't currently a standardized way to track the "hardness" of a problem—either for human formalizers or for Automated Theorem Provers (ATP).

The Proposal I suggest implementing an attribute system that allows contributors to tag conjectures with:

Complexity Tier (1-5): A scale from "Introductory/Trivial" to "Grand Challenge/Open Problem."

ATP Status: Metadata to track if the conjecture has been solved by systems like AlphaProof, Aesop, or Hammer, including the "search budget" or tactics used.

Formalization Effort: A metric for the complexity of the Lean statement itself (e.g., number of dependencies or definitions involved).

Example Usage:

Lean

@[difficulty { tier := 3, atp := "AlphaProof", formalization := "medium" }]
conjecture riemann_hypothesis : ...
Why this is useful for the project:

Curriculum Learning: It enables the creation of structured datasets for training AI models on a gradient of difficulty.

Gap Analysis: Helps identify which mathematical areas (via AMS codes) are currently most resistant to automation.

Benchmarking: Provides a native way to treat the repo as a living leaderboard for new formalization agents and tactic-suggestion models.

Implementation Plan: I can extend the existing attribute logic in Util/ to support these fields. This would allow external scripts to easily parse .lean files to generate progress reports or filtered datasets.

I'm happy to put together a PR for the attribute definitions if this aligns with the current roadmap for the repository.

Start by reviewing the existing attribute logic in Util/ and representative .lean conjecture declarations. Clarify the project roadmap and the intended schema for difficulty tiers, ATP status, and formalization effort before implementing anything; done means the agreed metadata can be applied to conjectures and parsed by external scripts.

Written by the indexing model from the issue text.