Questioning
You are answering a question directly and concisely using the research process. No documents are created by default — the answer is the deliverable.
When to Use
This skill activates when:
- User invokes
/questioncommand - Another skill references
desplega:questioning - User asks a focused question that doesn't need a full research document
Philosophy
This is the fastest path from question to answer. Unlike /research (which documents comprehensively) or /brainstorm (which explores interactively), /question gets straight to the point:
- Hear the question
- Investigate as needed
- Answer inline
- Offer next steps
No ceremony — no autonomy prompts, no preference setup, no working agreement. Just answer the question.
Process
Step 1: Analyze the Question
Classify the question to determine what investigation is needed:
| Question Type | Investigation Needed | Example | |---------------|---------------------|---------| | Factual/locational | Quick codebase search | "Where is the auth middleware defined?" | | Conceptual/how | Read relevant files | "How does the plugin system discover skills?" | | Why/root cause | Deep read + history | "Why does brainstorming default to verbose?" | | Comparative | Read multiple areas | "What's the difference between research and question skills?" | | External/library | context7 or web search | "How does Bun's SQLite driver handle transactions?" |
Step 2: Investigate
Based on the question type, use the appropriate tools. Spawn sub-agents only when needed — many questions can be answered by reading a few files directly.
For codebase questions:
- Read directly mentioned files first (use Read tool WITHOUT limit/offset)
- Use codebase-locator agent if you need to find WHERE something lives
- Use codebase-analyzer agent if you need to understand HOW something works
- Use codebase-pattern-finder agent if you need examples of a pattern
For library/framework questions:
- Use context7 MCP to fetch documentation (
resolve-library-id→query-docs)
For external/web questions:
- Use web-search-researcher agent for documentation or examples
Efficiency rule: If you can answer by reading 1-3 files, just read them. Don't spawn sub-agents for simple lookups.
Step 3: Answer
Present the answer as inline text (not a document). Structure it naturally based on the question:
- Short answers: 1-3 sentences with a file:line reference
- Medium answers: A paragraph or two with key references
- Detailed answers: Structured with headings if needed, but keep it focused
Unlike research, you MAY:
- Suggest improvements if the question implies a problem
- Perform root cause analysis if the question asks "why"
- Give opinions when asked ("which approach is better?")
- Be direct and opinionated rather than exhaustively neutral
Always include:
- Specific
file:linereferences for any claims about the codebase - Code snippets when they clarify the answer (keep them short)
Step 4: Handoff
After answering, use AskUserQuestion with:
| Question | Options |
|----------|---------|
| "What would you like to do next?" | 1. Ask another question, 2. Save this answer to thoughts, 3. Start a brainstorm from this topic (→ /brainstorm), 4. Start research from this topic (→ /research), 5. Done |
Based on the answer:
- Ask another question: Use AskUserQuestion to ask "What's your next question?" and loop back to Step 1
- Save this answer: Write the Q&A to
thoughts/<user>/questions/YYYY-MM-DD-<topic>.mdusing the template atcc-plugin/base/skills/questioning/template.md. Path selection: use the user's name if known, fall back tothoughts/shared/questions/ - Brainstorm: Suggest
/brainstorm <topic>with the question's topic as context - Research: Suggest
/research <topic>with the question's topic as context - Done: No further action
Looping Behavior
When the user selects "Ask another question," the skill loops:
- Ask for the next question via AskUserQuestion
- Investigate and answer (Steps 1-3)
- Present handoff options again (Step 4)
Each iteration is independent — no state accumulates between questions unless the user explicitly connects them.
Learning Capture
OPTIONAL SUB-SKILL: If significant insights, patterns, gotchas, or decisions emerged during this workflow, consider using desplega:learning to capture them via /learning capture. Focus on learnings that would help someone else in a future session.
What This Skill is NOT
- Not research: No comprehensive document, no frontmatter ceremony, no multi-section output
- Not brainstorming: No Socratic Q&A loop, no progressive document
- Not a chatbot: Each question gets proper investigation with codebase evidence, not surface-level responses