qa-appender
Original:🇨🇳 Chinese
Translated
Intelligent Q&A Appender that appends Q&A content from conversations to existing notes or creates new independent cards. Adopting the C+I structure (Insight + Context), it resolves the conflict between "unintelligible after simplification" and "too verbose without simplification". Triggers: /qa, /ask
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npx skill4agent add qingchunwuhui/xianfengaiskills qa-appenderTags
Translated version includes tags in frontmatterSKILL.md Content (Chinese)
View Translation Comparison →Q&A Appender
Role: Knowledge Referee, which determines the attribution of Q&A content and appends it in the optimal format.
Core Responsibilities
Single Responsibility: Append Q&A content from conversations to existing notes or create new independent cards in the C+I structure.
Usage Scenarios
Trigger Commands: or
/qa/askApplicable Scenarios:
- Have specific doubts (What/Why/How) about a certain point in an existing document
- Received answers through conversations
- Need to record the Q&A in notes
Core Logic: Knowledge Classification
I will act as a "Knowledge Referee" to determine the attribution of the Q&A:
- Context Heavy: Unintelligible without the original context → Append to the end of the original text
- Atomic Concept: Universal concept that can be understood independently of the original text → Generate an independent knowledge card
For detailed classification criteria, see:
references/classification_guide.mdWorkflow
When you input or , I will:
/qa/ask-
Intelligent Session Range Recognition
- Automatic Recognition: Analyze recent conversations to identify the current discussion topic and question boundaries
- Key Signals:
- Time point when the user raised a new question
- Topic transition markers (e.g., "Additionally", "Another question")
- Problem resolution markers (e.g., "Okay", "Got it", "Resolved")
- Extraction Principle: Only extract continuous conversation segments relevant to the current question, avoid including irrelevant content
- Intelligent Judgment:
- If it's a single Q&A (1-3 rounds): Extract the Q&A
- If it's a complex discussion (4-10 rounds): Extract the complete discussion process
- If it exceeds 10 rounds: Prompt the user to confirm whether to include all content
-
Read Classification Criteria
- Must read before execution
references/classification_guide.md - Determine the attribution of the Q&A (Context Heavy vs Atomic Concept)
- Must read
-
Determine Processing Method
- Context Heavy: Append the section at the end of the original text
## 💡 Practical Q&A - Atomic Concept: Generate an independent knowledge card
- Context Heavy: Append the
-
Apply C+I Structure
- Read to obtain complete specifications
references/ci_structure.md - Strictly organize content according to the template format
- Logic (Insight) comes first, Context comes below
- Read
-
Obtain Confirmation
- Provide the following information at once:
- Session Range: Clearly inform which rounds of conversations were extracted (e.g., "Extracted the last 3 rounds of conversations")
- Judgment Result: Context Heavy or Atomic Concept
- Judgment Reason: Why this judgment was made
- Target File Path: Which file will be written to
- Prohibited: Displaying a complete preview of the content to be appended (the preview is too long and interferes with reading)
- Confirm only once and wait for the user's reply
- Provide the following information at once:
-
Write to File
- Directly write to the file after user confirmation
- Prohibited: Displaying the preview or confirming again
- Briefly inform the result after writing
Execution Specifications (Important)
Intelligent Range Recognition:
- ✅ Automatically identify relevant conversation segments and avoid extracting irrelevant content
- ✅ Clearly inform the extracted session range during the confirmation phase
- ❌ Do not extract the entire conversation history
One-Time Confirmation Principle:
- ✅ Confirm only once in step 5
- ❌ Prohibited to confirm again in step 6
No Preview Principle:
- ✅ Only display the session range, judgment result, and brief reason
- ❌ Prohibited to display the complete preview of the content to be appended
- Reason: Long preview content interferes with reading, and users trust the judgment logic
Efficient Execution:
Step 1: Intelligent session range recognition (internal processing)
Step 2-4: Read + analyze + organize content (internal processing)
Step 5: Output session range + judgment result + wait for confirmation (once)
Step 6: Directly write + brief notification (completed)C+I Structure Overview
Adopting the C+I structure resolves the conflict between "unintelligible after simplification" and "too verbose without simplification":
- C (Context) - Original Context: The complete conversation at that time, including code, error messages, and parameters
- I (Insight) - Key Takeaway: A one-sentence universal principle without specific cases
For complete instructions and templates, see:
references/ci_structure.mdCollaboration with Other Skills
Upstream:
- : Generates basic notes
conversation-extractor - : Generates process documents
process-doc-generator
Downstream:
- The appended document can be further expanded using
process-doc-generator
Resource Files
- C+I Structure Details: references/ci_structure.md
- Classification Guide: references/classification_guide.md