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    Clearcut: the answer first, detail only when you ask

    1

    Explains code, errors and concepts in one sentence first, then four short points. A full deep dive only when you ask for it.

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    Clearcut: the answer first, detail only when you ask

    Clearcut: the answer first, detail only when you ask

    Example session with this skill installed

    Clearcut

    function throttle(fn, wait) {
  let inThrottle, lastFn, lastTime;
  return function() {
    const context = this, args = arguments;
    if (!inThrottle) {
      fn.apply(context, args);
      lastTime = Date.now();
      inThrottle = true;
    } else {
      clearTimeout(lastFn);
      lastFn = setTimeout(function() {
        if (Date.now() - lastTime >= wait) {
          fn.apply(context, args);
          lastTime = Date.now();
        }
      }, Math.max(wait - (Date.now() - lastTime), 0));
    }
  }
}
    • Read your context and instructions
    • Compiled the clearcut

    throttle ensures a function is called at most once every wait milliseconds, even if triggered repeatedly.

    Key points
    • Uses inThrottle flag and lastTime timestamp to track execution windows
    • setTimeout schedules the final trailing call if the event stops during the wait period
    • Common uses: scroll event listeners, window resizing, mouse movements
    • Gotcha: memory leaks: if not cleaned up, the internal lastFn timer might persist after component unmount
    • Alternative: debounce (waits until silence) vs throttle (limits frequency during activity)

    Want deeper detail on the leading/trailing edge logic, this context binding, or a simpler implementation?

    Next steps

    1. Check if you need a leading or trailing edge execution for your specific UI event.
    2. Ensure you have a way to cancel the internal lastFn timer if the parent component unmounts.
    3. Ask "go deeper on context binding" if you are using this inside a class component or specific object scope.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Technical debt and unfamiliar codebases slow down development when every explanation is a wall of text. Most AI responses bury the answer under conversational filler and generic introductions. This skill enforces a strict, layered response structure designed for speed and clarity. It eliminates greeting bloat and provides immediate answers to code, errors, and architectural patterns.

    What it does

    • Layered Explanations delivers a one-sentence primary answer followed by high-signal bullet points.
    • Context Awareness identifies technology stacks from READMEs and manifests to tailor technical depth.
    • Error explanations give the most common cause and a quick fix for an error message or stack trace.
    • Pattern Analysis explains complex architectural concepts like dependency injection or debouncing without the fluff.
    • Deep-Dive Readiness prepares a comprehensive mechanism walkthrough available only upon explicit request.

    How it works

    1. Targeting Invoke the skill using Clearcut followed by a code snippet, file path, or error message.
    2. Layering The agent generates a 25-word maximum summary then 3-5 critical technical bullets.
    3. Exploration Review the provided "gotchas" and usage patterns to solve the immediate blocker.
    4. Drill-down Reply with "go deeper" or a specific question to trigger the full implementation walkthrough.

    Frameworks & tools

    This skill is language-agnostic and works with any framework. It reads the project's README and manifest for context when they exist.

    Why this beats prompting it yourself

    Standard prompts often produce verbose, conversational responses that force you to hunt for the actual fix. This skill uses a strict anti-pattern filter to remove filler and puts the answer in the first sentence.

    Use cases

    • Code Onboarding quickly understand a legacy function or unfamiliar file in a new repo.
    • Rapid Debugging get the specific cause and fix for a cryptic runtime error or stack trace.
    • Syntax Refresh recall the nuances of hooks, closures, or library-specific APIs.
    • Concept Mapping bridge the gap between architectural patterns and concrete implementation.

    Known limitations

    Does not perform live code execution or external API lookups. Deep-dive layers require a separate follow-up prompt to maintain token efficiency.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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