ibs / that / symptoms
General SOP for common requests related to please, risk, demonstrating.
npx skills add ECNU-ICALK/AutoSkill --skill ibs-that-symptoms --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.
# ibs / that / symptoms General SOP for common requests related to please, risk, demonstrating. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: d6ab9103f9551c7f701cf32f4e0e74b2.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) make it short for presentation - Protein Preparation: 8) Preparing a protein for molecular docking, especially for rho kinase (ROCK), involves a meticulous series of steps aimed at ensuring its structural integrity and suitability for computational analysis. Firstly, the crystal structure of rho kinase is retrieved from a reliable protein structure database like the Protein Data Bank (PDB), ensuring high resolution and relevant ligands or co-factors if needed. Subsequently, the protein structure undergoes thorough preparation, which includes removing water molecules, heteroatoms, and any extraneous entities not per
- Prompt
- Triggers
- Examples
- Example 1
What does the ibs / that / symptoms skill do?
General SOP for common requests related to please, risk, demonstrating.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill ibs-that-symptoms --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.