formula-derivation
Skill54 starsChanged 5 months agoMITView on GitHub
Structure and derive research formulas when the user wants to 推导公式, derive a theory line, build equations from a problem statement, clarify assumptions, separate formal derivation from remarks, or turn messy theory notes into a paper-ready derivation skeleton. Use for research-style formula development, not for fully rigorous theorem proving once the claim is already fixed.
7 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- sjtuytc/ResearchMathAgenttheir own version, first seen Oct 20, 2026
- yvesory/academic-research-suitetheir own version, first seen Oct 9, 2026
- talhaMah56/claude_skillstheir own version, first seen Sep 12, 2026
- wanshuiyin/Auto-claude-code-research-in-sleeptheir own version, first seen Jul 15, 2026
- catalsqlb-cmd/Prism-Hedited, first seen May 29, 2026
- Chanw-research/claude-code-paper-writingtheir own version, first seen May 10, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- catalsqlb-cmd/Prism-H★ 1698% same
Wrote their own version · 6
- wanshuiyin/Auto-claude-code-research-in-sleep★ 19ksame name
- Chanw-research/claude-code-paper-writing★ 42same name
- sjtuytc/ResearchMathAgent★ 35same name
- yvesory/academic-research-suite★ 9same name
- raja21068/AutoResearch★ 2same name
- talhaMah56/claude_skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository27 other files it gives its agents.
- alphaxivSkill
- arxivSkill
- doc-coauthoringSkill
- docxSkill
- drawio-diagramSkill
- figure-descriptionSkill
- grant-proposalSkill
- mmx-cliSkill
- mock-reviewSkill
- novelty-checkSkill
- paper-readingSkill
- pdfSkill
- phd-benchmark-paper-templateSkill
- phd-figure-designerSkill
- phd-idea-evaluatorSkill
- phd-intro-drafterSkill
- phd-pre-submission-reviewerSkill
- phd-tech-paper-templateSkill
- phd-vibe-research-workflowSkill
- pptxSkill
- proof-writerSkill
- research-litSkill
- research-survey-loopSkill
- research-wikiSkill
- theme-factorySkill
- update-source-mapSkill
- xlsxSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
20 rules. 1 is common, 17 are distinctive, and 2 are very specific to this project.
1
Common
Most of the 7 edited versions we read keep these.
17
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this skill when the task is not merely to prove a finished theorem, but to build the derivation itself:
- Distinctive: line 24
Prefer one of these outputs:
- Common: line 44
Do not start symbolic manipulation before this is fixed.
- Very specific: line 57
If the current notes use a narrower quantity (c_i, throughput, delay, CW, etc.), decide whether it is:
- Distinctive: line 71
Do not introduce hidden assumptions mid-derivation unless they are clearly marked as extra local assumptions.
- Distinctive: line 75
Every nontrivial part of the derivation must be labeled mentally as one of:
- Distinctive: line 82
Never mix these without signaling the change.
- Distinctive: line 86
If the goal is to split a quantity into components, start from the global quantity and then differentiate / decompose.
- Distinctive: line 98
Do not present the decomposition as if it appeared magically from one local variable itself.
- Distinctive: line 102
If the theory must cover both a simplified regime and a more general regime, do not write two unrelated stories.
- Distinctive: line 114
If the true object is state dependent, adaptive, vector-valued, or otherwise complicated, but a theorem needs a simpler parameterization, …
- Distinctive: line 119
Use language such as:
- Distinctive: line 126
Do not let the simplified case silently replace the real conceptual object.
- Distinctive: line 135
If a section starts to read like an internal lecture note, split it into:
- Distinctive: line 156
When the user is unsure how to start, try one of these common patterns:
- Distinctive: line 158
Definition -> substitution -> simplification: Use when the target formula is mostly algebraic.
- Distinctive: line 160
Global quantity -> perturbation -> decomposition: Use when the target needs direct / indirect, private / external, or local / global …
- Distinctive: line 162
Primitive law -> intermediate variable -> target expression: Use when deriving from a physical principle, conservation law, or …
- Distinctive: line 164
Exact model -> approximation -> interpretable closed form: Use when the exact formula is too heavy and a paper needs a usable surrogate.
- Very specific: line 191
Use formula-derivation when the user says things like:
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Formula Derivation
Use this skill when the task is not merely to prove a finished theorem, but to build the derivation itself:
- define the right object,
- decide what should be assumed,
- determine what is identity vs proposition vs approximation,
- connect simple and general regimes without splitting into two unrelated stories,
- and turn messy notes into a derivation line that can later be written into a paper.
Do not use this skill as a replacement for strict proof writing once the exact claim is already fixed and the user wants a theorem-proof package. In that case, stay focused on clarifying the derivation boundary, assumptions, and missing steps rather than pretending the proof is already complete.
Core Principle
The derivation must be built around one invariant object. Do not start from scattered formulas. Start from the object that survives across regimes, then derive proxies, decompositions, and interpretations from it.
What to Produce
Prefer one of these outputs:
- a mainline derivation note for internal alignment;
- a paper-style theory draft with tighter narrative;
- a blocker report if the current notes cannot support a coherent derivation.
Workflow
1. Freeze the Target
State explicitly:
- what phenomenon is being explained;
- what claim is being supported;
- whether the goal is:
- identity / algebra,
- local comparative statics,
- approximation,
- or mechanism interpretation.
Do not start symbolic manipulation before this is fixed.
2. Choose the Invariant Object
Find the single quantity that should remain meaningful across regimes.
Examples:
- objective / loss / utility
- total energy / cost / welfare
- state variable / conserved quantity / effective rate
- expected performance metric
If the current notes use a narrower quantity (c_i, throughput, delay, CW, etc.), decide whether it is:
- the true top-level object,
- or only a proxy / slice / approximation.
3. Put Assumptions and Notation First
Before deriving, list:
- assumptions;
- notation;
- regime boundaries;
- which quantities are fixed and which are state dependent.
Do not introduce hidden assumptions mid-derivation unless they are clearly marked as extra local assumptions.
4. Classify Every Step
Every nontrivial part of the derivation must be labeled mentally as one of:
- identity: exact algebraic reformulation;
- proposition: a claim requiring conditions;
- approximation: model simplification or surrogate;
- interpretation: prose-level explanation of what the formula means.
Never mix these without signaling the change.
5. Derive from the Global Quantity When Splitting Costs
If the goal is to split a quantity into components, start from the global quantity and then differentiate / decompose.
Pattern:
- define the global quantity, e.g.
W = \sum_j \Gamma_j; - perturb one local variable, e.g.
c_i; - compute the marginal social effect;
- split the result into:
- direct term,
- indirect term,
- or private / external terms if that distinction is part of the model.
Do not present the decomposition as if it appeared magically from one local variable itself. The split must come from the effect of changing that variable on the chosen global quantity.
6. Keep Special Cases and General Cases in One Line
If the theory must cover both a simplified regime and a more general regime, do not write two unrelated stories.
Use this pattern:
- same invariant object across all regimes;
- special case: some terms vanish or collapse;
- general case: the same object gains extra structure.
This prevents the simple case from looking like an exception and the general case from looking like a different theory.
7. Treat Simplified Parameters as Analysis Slices
If the true object is state dependent, adaptive, vector-valued, or otherwise complicated, but a theorem needs a simpler parameterization, write:
- the general object first;
- then define the simpler case as a tractable slice.
Use language such as:
- frozen-parameter approximation;
- constant-coefficient slice;
- local linearization;
- reduced-order case.
Do not let the simplified case silently replace the real conceptual object.
8. Separate Main Text from Remarks
For derivations intended for papers:
- the main derivation should contain only equations and immediate mathematical consequences;
- explanatory prose, intuition, scenario reading, and caveats should be moved to Remark / Discussion / Scope paragraphs.
If a section starts to read like an internal lecture note, split it into:
- derivation body;
- remark.
9. Write Boundaries Explicitly
At the end, state:
- what the derivation actually proves;
- what remains approximation;
- what should not be claimed.
Especially guard against:
- turning a local proposition into a universal theorem;
- letting an interpretation sound like a proof;
- hiding a proxy as if it were the true quantity.
Common Derivation Patterns
When the user is unsure how to start, try one of these common patterns:
- Definition -> substitution -> simplification Use when the target formula is mostly algebraic.
- Global quantity -> perturbation -> decomposition Use when the target needs direct / indirect, private / external, or local / global splitting.
- Primitive law -> intermediate variable -> target expression Use when deriving from a physical principle, conservation law, or probabilistic identity.
- Exact model -> approximation -> interpretable closed form Use when the exact formula is too heavy and a paper needs a usable surrogate.
- General dynamic object -> frozen slice -> theorem -> return to general case Use when the real system is adaptive or state dependent, but the proof needs a simpler slice.
Recommended Output Structure
For an internal derivation note:
- Target
- Invariant object
- Assumptions and notation
- Main derivation
- Regime interpretation
- Approximations and open risks
For a paper-style theory section:
- Unified object
- Formal proxy and assumptions
- Special-case to general-case decomposition
- Reward / objective reformulation
- Local theorem or proposition
- State-dependent extension
- Scope and non-claims
Boundary With Finished Proofs
Use formula-derivation when the user says things like:
- “我不知道怎么起这条推导主线”
- “这个公式到底该从哪个量出发”
- “帮我把理论搭顺”
- “把说明文档变成可写进论文的公式文档”
The derivation is usually mature enough for a finished theorem-proof package only after:
- the exact claim is already fixed,
- the assumptions are stable,
- and the task is now to prove or refute that claim rigorously.
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