formula-derivation
Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.
npx skills add majiayu000/claude-skill-registry --skill formula-derivation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Formula Derivation: Research Theory Line Construction Build an honest derivation package, not a fake polished theorem story. ## Constants - DEFAULT_DERIVATION_DOC = `DERIVATION_PACKAGE.md` in project root - STATUS = `COHERENT AS STATED | COHERENT AFTER REFRAMING / EXTRA ASSUMPTION | NOT YET COHERENT` ## Context: $ARGUMENTS ## Goal Produce exactly one of: 1. a coherent derivation package for the original target 2. a reframed derivation package with corrected object / assumptions / scope 3. a blocker report explaining why the current notes cannot yet support a coherent derivation ## Inputs Extract and normalize: - the target phenomenon, formula, relation, or theory line - the intended role of the derivation: - exact identity / algebra - proposition / local theorem - approximation - mechanism interpretation - explicit assumptions - notation and definitions - any user-provided formula chain, sketch, messy notes, or current draft - nearby local theory files if the request points to them - desired output style if specified: - internal alignment note - paper-style theory draft - blocker report If the target, object, notation, or assumptions are ambiguous, state the exact interpretation
- Constants
- Context: $ARGUMENTS
- Goal
- Inputs
- Workflow
- Step 1: Gather Derivation Context
- Step 2: Freeze the Target
- Step 3: Choose the Invariant Object
- Step 4: Normalize Assumptions and Notation
- Step 5: Classify the Derivation Steps
- Step 6: Build a Derivation Map
- Step 7: Write the Derivation Document
- Step 8: Final Verification
- Required File Structure
What does the formula-derivation skill do?
Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill formula-derivation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.