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 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill formula-derivation
Build an honest derivation package, not a fake polished theorem story.
DERIVATION_PACKAGE.md in project rootCOHERENT AS STATED | COHERENT AFTER REFRAMING / EXTRA ASSUMPTION | NOT YET COHERENTProduce exactly one of:
Extract and normalize:
If the target, object, notation, or assumptions are ambiguous, state the exact interpretation you are using before deriving anything.
Determine the target derivation file with this priority:
DERIVATION_PACKAGE.md in project root as the default targetRead the relevant local context:
Extract:
State explicitly:
Do not start symbolic manipulation before this is fixed.
Identify the single quantity or conceptual object that should organize the derivation.
Typical possibilities include:
If the current notes start from a narrower quantity, decide explicitly whether it is:
Do not let a convenient proxy silently replace the actual conceptual object.
Restate:
Identify:
Preserve the user's original notation unless a cleanup is necessary for coherence.
If you adopt a cleaner internal formulation, keep that as a derivation device rather than silently replacing the user's target.
For every nontrivial step, determine whether it is:
Never merge these categories without signaling the transition.
If one part is only interpretive, do not present it as if it were mathematically proved.
Choose a derivation strategy, for example:
Then write a derivation map:
If the derivation needs a decomposition, derive it from the chosen global quantity.
Do not make a split appear magically from one local variable itself.
Write to the chosen target derivation file.
If the target derivation file already exists:
If the user does not specify a target, default to DERIVATION_PACKAGE.md in project root.
Do NOT write directly into paper sections or appendix .tex files unless the user explicitly asks for that target.
The derivation package must include:
Writing rules:
Before finishing the target derivation file, verify:
If the derivation still lacks a coherent object, stable assumptions, or an honest path from premises to result, downgrade the status and write a blocker report instead of forcing a clean story.
Write the target derivation file using this structure:
# Derivation Package
## Target
[what is being derived or explained]
## Status
COHERENT AS STATED / COHERENT AFTER REFRAMING / NOT YET COHERENT
## Invariant Object
[top-level quantity organizing the derivation]
## Assumptions
- ...
## Notation
- ...
## Derivation Strategy
[chosen route and why]
## Derivation Map
1. Target depends on ...
2. Intermediate step A uses ...
3. Approximation enters at ...
## Main Derivation
Step 1. ...
Step 2. ...
...
## Remarks and Interpretation
- ...
## Boundaries and Non-Claims
- ...
## Open Risks
- ...
Write the full structure above with a clean derivation package.
Write:
Write:
Status: NOT YET COHERENTproof-writerUse formula-derivation when the user says things like:
Use proof-writer only after:
After writing the target derivation file, respond briefly with:
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Take wanshuiyin/formula-derivation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.