qa-extractor
Skill2 starsChanged 38 days agoMITView on GitHub
Use when extracting verbatim answers to specific questions from a long document, with optional translation of extracted text
In this repository15 other files it gives its agents.
- notemdproSkill
- batch-processorSkill
- concept-extractorSkill
- content-generatorSkill
- diagram-generatorSkill
- formula-healerSkill
- link-analyzerSkill
- mermaid-healerSkill
- mermaid-summarizerSkill
- selection-processorSkill
- system-architectureSkill
- test-driven-developmentSkill
- text-translatorSkill
- web-researcherSkill
- workflow-runnerSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 184
Specific questions: Use clear, specific questions
- Distinctive: line 186
Check output: Always verify extracted answers
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
NoteMD Pro - Text Extraction (Q&A)
Overview
This feature extracts specific answers from markdown files based on user-configured questions. It uses LLM to analyze the content and provide precise answers to each question.
When to Use
- Q&A extraction: Get specific answers from long documents
- Data mining: Extract structured information from unstructured text
- Survey analysis: Parse responses to multiple questions
- Research: Pull key findings from papers
Function Call Chain
extractOriginalText (extractOriginalText.ts)
├── read_file(inputPath)
├── settings.extractQuestions (split by newlines)
├── getProviderAndModelForTask('extractOriginalText')
├── IF mergedMode
│ └── callLLM with all questions combined
├── ELSE (individual mode)
│ └── for each question
│ └── callLLM with single question
├── Format results
└── save to output file
├── mkdir_p(outputFolderPath)
└── write_file(outputPath, content)Key Function (from extractOriginalText.ts)
extractOriginalText
Extracts answers to configured questions from a file.
export async function extractOriginalText(
plugin: NotemdPlugin,
inputPath: string,
reporter: ProgressReporter,
): Promise<void>;
// Outputs: File with Q&A extractedSettings
Question Configuration
| Setting | Description |
extractQuestions | Questions to ask (one per line) |
extractOriginalTextMergedMode | Process all questions in one LLM call |
Provider Settings
| Setting | Description |
extractOriginalTextProvider | LLM provider for extraction |
extractOriginalTextModel | Model for extraction |
extractOriginalTextLanguage | Language for output |
Contextual Context (Macro Settings)
| Setting | Description |
enableFocusedLearning | Inject macro user domain preferences globally |
focusedLearningDomain | The specific domain context (e.g., "Quantum Physics") |
Output Settings
| Setting | Description |
extractOriginalTextUseCustomOutput | Use custom output path |
extractOriginalTextCustomPath | Custom output folder |
extractOriginalTextCustomSuffix | Custom filename suffix |
Translation
| Setting | Description |
translateExtractOriginalTextOutput | Translate extracted text |
Prompt Templates (extractOriginalText)
Individual Mode
You are a strict Data Extraction and Verification Agent.
Your task is to extract the answer to the user's question from the provided reference content.
Reference Content:
{REFERENCE_CONTENT}
User Question:
{USER_INPUT}
Instructions:
1. Answer ONLY based on the reference content provided
2. If the answer is not found, state "Answer not found in the provided text"
3. Be precise and concise
4. Include relevant context if necessaryMerged Mode
You are a strict Data Extraction and Verification Agent.
Your task is to extract answers to ALL questions from the provided reference content.
Reference Content:
{REFERENCE_CONTENT}
Questions:
{USER_INPUT}
Instructions:
1. Answer EACH question based ONLY on the reference content
2. Format each answer as: "Q: [question] A: [answer]"
3. If the answer is not found for a question, state "Answer not found"
4. Be precise and conciseOutput Format
Individual Mode Output
Q: [Question 1]
A: [Answer 1]
Q: [Question 2]
A: [Answer 2]Merged Mode Output
1. [Question 1]
[Answer 1]
2. [Question 2]
[Answer 2]Processing Modes
Individual Mode (Default)
- Processes each question separately
- More accurate for complex questions
- Higher API usage
Merged Mode
- Combines all questions in one call
- Faster processing
- Less accurate for complex questions
Error Handling
Common Errors
- No questions configured
- Error: "No questions configured in settings for extraction"
- Solution: Add questions in plugin settings
- Empty file
- Error: Cannot extract from empty file
- Solution: Check source file content
- API errors
- Error: LLM API failure
- Solution: Check API key, network, retry
Best Practices
- Specific questions: Use clear, specific questions
- Limit questions: 5-10 questions per file works best
- Check output: Always verify extracted answers
Does it work?
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