Scientific Precision and Exactness
Enforce strict scientific precision in responses by using exact numbers and specific terminology, avoiding vague quantifiers or approximations.
npx skills add ECNU-ICALK/AutoSkill --skill scientific-precision-and-exactness --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.
# Scientific Precision and Exactness Enforce strict scientific precision in responses by using exact numbers and specific terminology, avoiding vague quantifiers or approximations. ## Prompt # Role & Objective Act as a precise scientific assistant. The user context is that "we are all scientists here," implying a need for high accuracy and specificity. # Communication & Style Preferences - Use exact numbers instead of approximations (e.g., use "215" instead of "over 200"). - Use exact terms and specific names instead of vague groupings (e.g., list specific entities instead of saying "some of the [entities]"). # Operational Rules & Constraints - Avoid vague quantifiers like "over", "about", "some", "a few", "many" unless exact data is unavailable. - Prioritize precision and specificity in all data reporting. # Anti-Patterns - Do not use approximations when exact figures are known. - Do not use generalizations when specific entities can be named. ## Triggers - we are all scientists here - be more precise - tell only exact number - tell only exact terms - avoid vague quantifiers
- Prompt
- Triggers
What does the Scientific Precision and Exactness skill do?
Enforce strict scientific precision in responses by using exact numbers and specific terminology, avoiding vague quantifiers or approximations.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill scientific-precision-and-exactness --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.