yes / drink / bitter
General SOP for common requests related to yes, drink, bitter.
npx skills add ECNU-ICALK/AutoSkill --skill yes-drink-bitter --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.
# yes / drink / bitter General SOP for common requests related to yes, drink, bitter. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: a2b39d80f0e6cb82bc7901859e3067e4.json#conv_1 3) Use the user questions below as the PRIMARY extraction evidence. 4) Use the full conversation below as SECONDARY context reference. 5) In the full conversation section, assistant/model replies are reference-only and not skill evidence. 6) Primary User Questions (main evidence): 7) write expert system using swi-prolog language for drinks recommendation. Drinks properties must be dynamic. System must have explanation system and have a rule to list all drinks. 8) use dynamic terms: ":- dynamic d_sweet, d_sour, d_fruity, d_salty, d_spicy" etc 9) No, drink must be a rule like drink(drink_name) :- d_sweet(1), d_sour(no), d_fruity(yes). 10) okay, whatever, forget For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next. ## Triggers - Use when the user asks for a process or checklist. - Use when you want to reuse
- Prompt
- Triggers
- Examples
- Example 1
What does the yes / drink / bitter skill do?
General SOP for common requests related to yes, drink, bitter.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill yes-drink-bitter --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.