formula-derivation
🤖 AI Summary
This agent takes a target formula or theory and either produces a coherent derivation package, reframes it with corrected assumptions, or generates a blocker report explaining why the current notes are insufficient.
How to Install
Claude Code:
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git && cp Auto-claude-code-research-in-sleep/skills/formula-derivation ~/.claude/skills/formula-derivation -r# 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 you are using before deriving anything.
## Workflow
### Step 1: Gather Derivation Context
Determine the target derivation file with this priority:
1. a file path explicitly specified by the user
2. a derivation draft already referenced in local notes
3. `DERIVATION_PACKAGE.md` in project root as the default target
Read the relevant local context:
- the chosen target derivation file, if it already exists
- any local theory notes, formula drafts, appendix notes, or files explicitly mentioned by the user
Extract:
- target formula / theory goal
- current formula chain
- assumptions
- notation
- known blockers
- desired output mode
### Step 2: Freeze the Target
State explicitly:
- what is being explained, derived, or supported
- whether the immediate goal is:
- identity / algebra
- proposition
- approximation
- interpretation
- what the derivation is expected to output in the end
Do not start symbolic manipulation before this is fixed.
### Step 3: Choose the Invariant Object
Identify the single quantity or conceptual object that should organize the derivation.
Typical possibilities include:
- objective / utility / loss
- total cost / energy / welfare
- conserved quantity / state variable
- expected metric / effective rate / effective cost
If the current notes start from a narrower quantity, decide explicitly whether it is:
- the true top-level object
- a proxy
- a local slice
- an approximation
Do not let a convenient proxy silently replace the actual conceptual object.
### Step 4: Normalize Assumptions and Notation
Restate:
- all assumptions
- all symbols
- regime boundaries or special cases
- which quantities are fixed, adaptive, or state dependent
Identify:
- hidden assumptions
- undefined notation
- scope ambiguities
- whether t
Details
| Category | Design → ui |
| Source | wanshuiyin/Auto-claude-code-research-in-sleep |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 12.5K |
| Est. per Skill | N/A (shared across 74 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
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