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Extracts and categorizes requirements from PDFs, Word docs, transcripts, specs, and web content using pattern matching and outputs structured YAML.
How this skill is triggered — by the user, by Claude, or both
Slash command
/requirements-elicitation:document-extractionThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Extract requirements from existing documentation sources for systematic requirement mining.
Extract requirements from existing documentation sources for systematic requirement mining.
Keywords: extract requirements, document mining, PDF requirements, transcript analysis, parse document, existing documentation, legacy requirements, competitive analysis
Invoke this skill when:
| Type | Extension | Extraction Method |
|---|---|---|
| Markdown | .md | Direct Read |
| Text | .txt | Direct Read |
| Read tool (PDF support) | ||
| Word | .docx | Read tool |
| Web Page | URL | WebFetch tool |
| Meeting Notes | .md, .txt | Transcript patterns |
| Specification | .md, .docx | Requirement patterns |
Analyze the document to determine extraction strategy:
document_assessment:
path: "{file path or URL}"
type: "{detected document type}"
size: "{approximate size}"
structure:
has_sections: true|false
has_lists: true|false
has_tables: true|false
quality:
formal_language: true|false
clear_requirements: true|false
needs_interpretation: true|false
Apply requirement detection patterns:
Explicit Requirement Markers:
- "The system shall..."
- "The system must..."
- "Users should be able to..."
- "REQ-XXX:"
- Numbered requirements (1.1, 1.2, etc.)
EARS Patterns:
- "When [trigger], the [system] shall [response]"
- "While [state], the [system] shall [behavior]"
- "Where [feature], the [system] shall [behavior]"
- "If [condition], then the [system] shall [response]"
Implicit Requirement Indicators:
- "It is important that..."
- "We need..."
- "The goal is to..."
- "Users expect..."
- "Performance should..."
For each identified requirement:
extracted_requirement:
id: REQ-{sequence}
text: "{cleaned requirement statement}"
source: document
source_file: "{file path}"
source_location: "{section/page/line}"
original_text: "{exact text from document}"
type: functional|non-functional|constraint|assumption
confidence: high|medium|low
extraction_method: explicit|pattern|inferred
needs_review: true|false
review_notes: "{why review needed}"
Categorize extracted requirements:
categories:
functional:
- features
- behaviors
- interactions
non_functional:
- performance
- security
- usability
- reliability
- scalability
constraints:
- technical
- business
- regulatory
assumptions:
- environmental
- user_behavior
- dependencies
Identify and merge duplicate requirements:
deduplication:
strategy: semantic_similarity
threshold: 0.8
action: merge|flag_for_review
merged_requirements:
- id: REQ-merged-001
sources: [REQ-001, REQ-015]
text: "{consolidated requirement}"
transcript_extraction:
focus_on:
- Action items
- Decisions made
- Requirements discussed
- Concerns raised
patterns:
- "We decided that..."
- "The requirement is..."
- "Action item:"
- "TODO:"
- "Need to..."
speaker_context:
- Note who said what
- Weight by speaker role
regulatory_extraction:
focus_on:
- Mandatory requirements ("shall", "must")
- Prohibited actions ("shall not", "must not")
- Conditional requirements ("if...then")
compliance_mapping:
- Reference section numbers
- Note effective dates
- Track version/revision
competitor_extraction:
focus_on:
- Feature descriptions
- User capabilities
- Unique selling points
output:
- Feature requirements
- Differentiation opportunities
- Gap identification
confidence: low # Based on external observation
legacy_extraction:
focus_on:
- Existing requirements
- System behaviors
- Integration points
modernization:
- Update terminology
- Convert to EARS format
- Flag deprecated requirements
extraction_result:
source:
file: "{path or URL}"
type: "{document type}"
extraction_date: "{ISO-8601}"
confidence: high|medium|low
statistics:
total_candidates: {number}
extracted: {number}
filtered: {number}
needs_review: {number}
requirements:
- id: REQ-{number}
text: "{requirement}"
type: functional|non-functional|constraint
source_location: "{section/page}"
confidence: high|medium|low
original_text: "{exact source text}"
review_items:
- requirement_id: REQ-{number}
reason: "{why review needed}"
suggestion: "{proposed action}"
metadata:
sections_processed: {number}
extraction_patterns_used: ["{pattern names}"]
guided_behavior:
document_selection: Human selects
extraction_strategy: AI suggests, human approves
each_requirement: AI highlights, human confirms
categorization: AI suggests, human validates
semi_auto_behavior:
document_selection: AI suggests priority, human approves list
extraction_strategy: AI chooses autonomously
requirements: AI extracts all, human reviews in batches
categorization: AI categorizes, human spot-checks
full_auto_behavior:
document_selection: AI processes all relevant
extraction_strategy: AI optimizes per document
requirements: AI extracts, deduplicates, categorizes
output: Full extraction report for final review
For related tasks, delegate to:
Save extraction results to:
.requirements/{domain}/documents/DOC-{filename}-{timestamp}.yaml
elicitation-methodology - Parent hub skillgap-analysis - Post-extraction completeness checkinginterview-conducting - Clarify extracted requirements with stakeholdersnpx claudepluginhub melodic-software/claude-code-plugins --plugin requirements-elicitationExtracts requirement candidates from PDFs, Markdown, Word docs, text files, and URLs. Categorizes by type, deduplicates across files, saves in YAML, and provides extraction summary.
Extracts requirements, user stories, bugs, and tasks from specs, PRDs, meeting notes, and design docs into structured work items. Use when capturing actionable items from existing documents.
Decomposes a connected doc (Notion, Google Doc, Confluence, etc.) into multiple intake-backlog entries for audit routing. Use when extracting insights, decisions, or questions from a single page.