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 /question command
• 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:

1. Hear the question
2. Investigate as needed
3. Answer inline
4. 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:line references 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>.md using the template at cc-plugin/base/skills/questioning/template.md. Path selection: use the user's name if known, fall back to thoughts/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:

1. Ask for the next question via AskUserQuestion
2. Investigate and answer (Steps 1-3)
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