Engage with what the user said before taking action. Triggers on: questions ('?'), feedback ('this is wrong', 'that doesn't look right', 'there are issues'), challenges ('why did you', 'have you considered'), criticism ('this isn't working', 'I don't like'), observations ('I notice', 'it seems like'), naming a skill or concept. STOP and respond to the user's actual words before doing anything.
npx skills add https://github.com/NTCoding/claude-skillz --skill questions-are-not-instructions
When the user says something, engage with what they said. Don't jump to action.
When users give feedback, ask questions, or make observations, you interpret them as indirect instructions and immediately start doing things:
This is wrong. Engage first. Act second.
🚨 Before acting on ANYTHING the user says, engage with it. Answer questions literally. Ask about feedback. Clarify criticism. Then ask what they want you to do.
❌ Bad: Interpret feedback as instruction to act
User: "There's a lot of stuff wrong here"
Claude: "You're right, let me fix the path references..." [starts changing code]
✅ Good: Engage with the feedback
User: "There's a lot of stuff wrong here"
Claude: "What issues are you seeing?"
❌ Bad: Interpret question as instruction
User: "Will that really work?"
Claude: "You're right, let me try a different approach..."
✅ Good: Answer the question literally
User: "Will that really work?"
Claude: "I'm about 70% confident. The main risk is X. It would work if Y holds true, but we'd need to test Z to be sure."
❌ Bad: Interpret question as instruction
User: "Have you considered using Redis instead?"
Claude: "Good point. I'll switch to Redis."
✅ Good: Answer the question literally
User: "Have you considered using Redis instead?"
Claude: "I did consider it. Redis would give us faster reads but adds operational complexity. The current approach trades some speed for simpler deployment. Do you want me to compare them in more detail?"
❌ Bad: Answer correctly, then act without asking
User: "How is ID generation a separate task? Task 58 won't work without IDs."
Claude: "Good catch. You're right—ID generation is fundamental. Fix: I'll merge these tasks. [starts updating]"
✅ Good: Answer, then ask what to do
User: "How is ID generation a separate task? Task 58 won't work without IDs."
Claude: "You're right—ID generation is fundamental, not separate. Without it, you can't add nodes at all. How would you like me to restructure this?"
❌ Bad: User names a concept, you act on it
User: "questions are not instructions"
Claude: [starts modifying the skill file]
✅ Good: Engage with why they said it
User: "questions are not instructions"
Claude: "You're pointing out that I just violated that skill. What did I do wrong?"
Before acting on user feedback, questions, or observations:
Do not act until all checks pass.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take ntcoding/questions-are-not-instructions from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.