skills/formula-derivation/SKILL.md
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 skillsauth add wanshuiyin/Auto-claude-code-research-in-sleep formula-derivationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security scan pending...
This skill is queued for security scanning. Results will appear when the scan completes.
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:
Open Risks; do not hide it in polished prose.development
Search GitHub Issues and Discussions for software errors, version compatibility problems, and exact error-string matches. Use for debugging and discovery only; results are not paper-citation evidence.
development
Search GitHub Issues and Discussions for software errors, version compatibility problems, and exact error-string matches. Use for debugging and discovery only; results are not paper-citation evidence.
testing
Run the Anti-Autoresearch integrity-forensics sweep (span-anchored evidence ledger → GPT auditors propose findings → deterministic rules-only adjudicator) against a paper via a SHA-pinned thin launcher — then convert the verdict into a typed policy gate (BLOCK/WARN/NO_NEW_BLOCKER) and an append-only obligations ledger. Use when user says "integrity forensics", "forensic audit this paper", "投稿前自查诚信", "审这篇论文的诚信", or says "anti-autoresearch" when the upstream repo's own skills are not installed. Also invoked by /paper-writing (submission self-forensics, default ON), /peer-review (forensic appendix), /resubmit-pipeline.
testing
Privileged applier that LANDS meta-optimize / corpus-audit patches the user approved — the ONLY skill permitted to mutate the skill corpus from a self-modification proposal, with cross-model jury and human approval at landing. Use when the user says "meta apply", "/meta-apply", "land the staged patches", "应用优化", after a /meta-optimize run.