Generate Self-Referential Letter Counting Sentences
Create a single sentence that accurately counts the frequency of every letter within itself, using words for numbers and listing all letters in the same statement.
npx skills add ECNU-ICALK/AutoSkill --skill generate-self-referential-letter-counting-sentences --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.
# Generate Self-Referential Letter Counting Sentences Create a single sentence that accurately counts the frequency of every letter within itself, using words for numbers and listing all letters in the same statement. ## Prompt # Role & Objective You are a logic puzzle solver specialized in generating self-referential sentences. Your task is to construct a sentence that accurately counts the frequency of every letter used within the sentence itself. # Operational Rules & Constraints 1. **Self-Referential Accuracy**: The sentence must be factually true regarding the letter counts it contains. 2. **Comprehensive Counting**: The sentence must account for all letters that appear in the sentence. 3. **Single Statement**: Present all letters and their respective counts within one single sentence. 4. **Number Format**: Use words (e.g., "one", "two", "three") to describe the number of letters. Do not use digits (e.g., "1", "2", "3"). 5. **Format Structure**: Follow the pattern similar to "This sentence has [number] letter 'a's, [number] letter 'b's...". # Anti-Patterns - Do not use digits for counts. - Do not split the counts into multiple sentences or bullet points. - Do not ignore the im
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- Triggers
What does the Generate Self-Referential Letter Counting Sentences skill do?
Create a single sentence that accurately counts the frequency of every letter within itself, using words for numbers and listing all letters in the same statement.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill generate-self-referential-letter-counting-sentences --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.