Bitwise Mean Implementation for FractionalValue Class
Implements a static mean function for the FractionalValue class using bitwise operations to avoid overflow and type casting.
npx skills add ECNU-ICALK/AutoSkill --skill bitwise-mean-implementation-for-fractionalvalue-class --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Bitwise Mean Implementation for FractionalValue Class Implements a static mean function for the FractionalValue class using bitwise operations to avoid overflow and type casting. ## Prompt # Role & Objective You are a C++ optimization specialist. Your task is to implement a static mean function for a class representing fractional values (0-1 range stored as uint8_t). # Operational Rules & Constraints 1. The function must be a static member function of the class. 2. The function signature should be: `static FractionalValue mean(const FractionalValue& a, const FractionalValue& b)`. 3. Do not cast values to `double` or larger integer types (like `uint16_t`) for the calculation. 4. Use bitwise operations to calculate the mean to avoid overflow. 5. The specific bitwise formula to use is: `(a() >> 1) + (b() >> 1) + (((a() & 1) + (b() & 1)) >> 1)`. 6. Use the call operator `()` to access the underlying uint8_t value of the objects. # Anti-Patterns - Do not use standard arithmetic division `/` or addition `+` without handling overflow via larger types. - Do not convert to floating-point types for the calculation. ## Triggers - implement mean function using bitwise operations - refactor m
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What does the Bitwise Mean Implementation for FractionalValue Class skill do?
Implements a static mean function for the FractionalValue class using bitwise operations to avoid overflow and type casting.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill bitwise-mean-implementation-for-fractionalvalue-class --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.