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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.

71

Quality

88%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Discovery

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong skill description that clearly articulates specific capabilities (structuring derivations, organizing assumptions, converting notes to paper-ready documents), includes natural trigger terms in both English and Chinese, and provides explicit 'Use when' guidance with helpful boundary conditions. The distinction from theorem proving and the specificity of the research derivation niche make it highly effective for skill selection.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'structures and derives research formulas', 'build a theory line', 'organize assumptions', 'turn scattered equations into a coherent derivation', 'rewrite theory notes into a paper-ready formula document'. These are concrete, actionable capabilities.

3 / 3

Completeness

Clearly answers both 'what' (structures and derives research formulas, organizes assumptions, turns scattered equations into coherent derivations) and 'when' (explicit 'Use when' clause specifying conditions: derivation target not fully fixed, main object needs choosing, user needs a derivation package rather than a finished proof).

3 / 3

Trigger Term Quality

Includes strong natural trigger terms: '推导公式' (Chinese for derive formulas), 'build a theory line', 'organize assumptions', 'scattered equations', 'coherent derivation', 'paper-ready formula document', 'derivation target', 'theorem proof'. Good coverage of terms a researcher would naturally use, including bilingual triggers.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche: research formula derivation and structuring, distinct from general math solving, theorem proving, or paper writing. The explicit contrast with 'finished theorem proof' helps disambiguate from adjacent skills. The bilingual trigger '推导公式' further narrows the scope.

3 / 3

Total

12

/

12

Passed

Implementation

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a strong, highly actionable skill for a specialized research task. Its greatest strengths are the clear 8-step workflow with explicit validation gates and the concrete output template. The main weakness is some redundancy across steps (the identity/proposition/approximation/interpretation classification is stated three times) and the monolithic structure that could benefit from splitting into overview + reference files for the template and decision criteria.

Suggestions

Consolidate the repeated identity/proposition/approximation/interpretation classification into a single reference point (e.g., a definitions section) and refer back to it from Steps 5, 7, and 8 instead of restating it each time.

Consider extracting the Required File Structure template and Output Modes into a separate reference file to reduce the main skill's length and improve progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is fairly long (~200+ lines) and some sections could be tightened—e.g., the detailed enumeration of derivation types (identity/proposition/approximation/interpretation) is repeated multiple times across Steps 5, 7, and 8. However, most content is domain-specific guidance that Claude wouldn't inherently know, so it's not padding with basic concepts. It's mostly efficient but has redundancy.

2 / 3

Actionability

The skill provides highly concrete, step-by-step instructions with specific file structures, exact status labels, explicit decision criteria (e.g., when to downgrade to blocker report), a complete markdown template for the output document, and clear trigger phrases for when to use this skill vs proof-writer. Every step tells Claude exactly what to do.

3 / 3

Workflow Clarity

The 8-step workflow is clearly sequenced with explicit validation checkpoints (Step 2 freezes the target before manipulation begins, Step 8 is a comprehensive verification checklist with feedback loop—downgrade status if verification fails). The workflow handles error cases (incoherent derivation → blocker report) and has clear decision points throughout.

3 / 3

Progressive Disclosure

The content is well-organized with clear sections and headers, but it's a monolithic document with no references to supporting files despite being quite long. The required file structure template, output modes, and relationship to proof-writer could potentially be split into separate reference files. However, for a standalone skill with no bundle, the internal organization is reasonable.

2 / 3

Total

10

/

12

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

9

/

11

Passed

Repository
wanshuiyin/Auto-claude-code-research-in-sleep
Reviewed

Table of Contents

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