What problem does it solve?
Researchers often have scattered formulas, messy notes, and half-finished theory lines that do not yet form a coherent derivation. This Skill organizes that material into a structured derivation package with a fixed target, a stable invariant object, normalized assumptions and notation, and honestly labeled steps, or reports exactly why coherence is not yet possible.
Core Features & Use Cases
- Derivation Structuring: Freezes the derivation target, chooses an invariant organizing object, and normalizes assumptions and notation before any symbolic manipulation.
- Step Classification: Labels every nontrivial step as identity, proposition, approximation, or interpretation so heuristic reasoning is never presented as proof.
- Honest Status Reporting: Outputs one of three statuses (COHERENT AS STATED, COHERENT AFTER REFRAMING, NOT YET COHERENT) and writes a blocker report instead of fabricating a clean story.
- Use Case: A graduate student has several pages of formula sketches for a theory section but no clear main line. The Skill produces a DERIVATION_PACKAGE.md with target, assumptions, derivation map, main steps, boundaries, and open risks, ready to be refined into a paper-ready theory draft.
Quick Start
Ask the assistant to turn your current formula notes into a coherent derivation package, for example: help me organize these theory notes into a derivation for the effective cost formula.
