| name | sdd-capture |
| description | This skill should be used when the user asks to "capture input", "save to RAG memory", "index a file", "store reference material", "capture document for context", or "add to knowledge base". It captures session inputs as RAG memory files with frontmatter, abstract, key takeaways, and full content. Workspace-aware routing sends captures to the active workspace's rag/ folder. Use this skill whenever the user mentions capture, RAG, memory indexing, or knowledge base storage. |
| license | MIT |
| metadata | {"version":"1.7.0"} |
SDD Capture — RAG Memory Capture with Auto-Detect [EXPLICIT]
Capture files as RAG memory entries with frontmatter, abstract, key takeaways, and workspace-aware routing.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty). The argument should be a file path.
Execution Flow
1. Run Capture Script
bash scripts/sdd-rag-capture.sh <file-path> [--global]
2. Auto-Detect File Type
Supported: text, markdown, HTML, images, audio, PDFs.
3. Generate RAG Entry
Creates rag-memory-of-{slug}.md with:
- Frontmatter: source, type, size, tags, captured timestamp
- Abstract + Key Takeaways + Relevant Insights
- Full Content (verbatim for text, structure summary for HTML, description for images)
4. Index
Updates .specify/rag-index.json with new entry.
5. Routing
- If workspace active: captures go to
workspace/{session}/rag/
- If no workspace or
--global: captures go to .specify/rag-memory/
Report
Captured!
File: <source-file>
RAG entry: <output-path>/rag-memory-of-{slug}.md
Type: <detected-type>
Size: <file-size>
Routed to: workspace/2026-03-30-task/rag/ (or .specify/rag-memory/)
Index: .specify/rag-index.json updated
Assumptions and Limits
| # | Assumption | Handling |
|---|
| 1 | File path provided as argument | If empty, ERROR with usage example. [EXPLICIT] |
| 2 | File exists and is readable | If not found, ERROR. [EXPLICIT] |
| 3 | Workspace-aware routing is default | Active workspace's rag/ used unless --global. [EXPLICIT] |
| 4 | RAG entry includes LLM-generated abstract | Requires AI inference for abstract/takeaways. [EXPLICIT] |
| 5 | Index file tracks all captures | .specify/rag-index.json updated atomically. [EXPLICIT] |
Edge Cases
| Scenario | Detection | Handling |
|---|
| No file argument | Empty $ARGUMENTS | ERROR with usage: /sdd:capture <file-path>. [EXPLICIT] |
| File not found | Path doesn't exist | ERROR with "file not found" message. [EXPLICIT] |
| Binary file (image/audio) | MIME type detection | Generate description instead of verbatim content. [EXPLICIT] |
| Very large file (>1MB) | File size check | Truncate content, note truncation in frontmatter. [INFERRED] |
| Duplicate capture | Same file already captured | Update existing entry, note "re-captured" in frontmatter. [EXPLICIT] |
Good vs Bad Example
Good: /sdd:capture docs/api-spec.md
Captured!
File: docs/api-spec.md
RAG entry: workspace/2026-03-30-task/rag/rag-memory-of-api-spec.md
Type: markdown | Size: 12KB
Abstract: API specification for REST endpoints...
Key Takeaways: 3 endpoints, JWT auth, rate limiting
Bad: Capture without metadata
x File copied without frontmatter
x No abstract or takeaways
x Not indexed in rag-index.json
Why: RAG capture must generate structured entries with frontmatter, abstract, and index updates for retrieval. [EXPLICIT]
Validation Gate
Before marking capture as complete, verify: [EXPLICIT]
