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How to handle natural language document requests—resolve friendly names to paths, then use appropriate tools for reading, searching, summarizing, or analyzing Word documents
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| name | Document Reading & Resolution Workflows |
| description | How to handle natural language document requests—resolve friendly names to paths, then use appropriate tools for reading, searching, summarizing, or analyzing Word documents |
| domain | document-operations, natural-language-interfaces |
| confidence | low |
| source | manual |
| tools | [{"name":"resolve_document","description":"Resolves a friendly document name (e.g., 'foo') + optional location hint to an absolute path","when":"User mentions a document by friendly name (not absolute path). Call this FIRST before other document tools"},{"name":"read_document","description":"Reads full text content from a .docx file at a resolved path","when":"User asks to read, show, open, or view a document. Use after resolve_document"},{"name":"search_document","description":"Searches for text within a .docx file and returns matching lines with line numbers","when":"User asks to search/find/look for specific text within a document. Use after resolve_document"},{"name":"get_document_metadata","description":"Returns file metadata (size, creation date, modification date) for a .docx file","when":"User asks about document properties (size, when modified, when created). Use after resolve_document"},{"name":"list_documents","description":"Lists all .docx files in a directory","when":"User asks what documents are in a location (desktop, downloads, etc.)"}] |
During a session, users frequently ask about Word documents using natural language: "Read the architecture doc on my desktop", "Summarize the status report I just downloaded", "Search for 'Q1 results' in the financial spreadsheet."
These requests fall into two categories:
Explicit path given: read_document("/absolute/path/to/file.docx")
→ Skip resolve_document, go straight to the target tool
Friendly name + optional location: "read foo from my desktop"
→ Requires resolution first (via resolve_document), then composition with a target tool
This skill teaches agents how to recognize friendly-name requests, resolve them correctly, and compose the right tool sequence for each intent.
Applies when: User mentions a document by friendly name (not absolute path)
Sequence:
resolve_document(name, location)status: "found" → Use resolved_path with target toolstatus: "ambiguous" → Present candidates to user, ask which onestatus: "not_found" → Explain search locations, suggest alternativesExample dialogue:
User: "Read the budget document on my desktop"
Agent step 1: resolve_document(name="budget", location="desktop")
Agent step 2: Returns { status: "found", resolved_path: "/Users/me/Desktop/budget.docx", ... }
Agent step 3: read_document(path="/Users/me/Desktop/budget.docx")
Agent step 4: Presents content to user
Parse user language for location keywords:
| User Language | Location Param |
|---|---|
| "on my desktop" | "desktop" |
| "in my downloads" / "I just downloaded" | "downloads" |
| "in my documents" / "in my docs" | "documents" |
| "in current directory" / "in this folder" / "here" |
"current" |
| "in /path/to/folder" | absolute/relative path as-is |
| No location mentioned | omit location param (tool searches all common locations) |
Once document is resolved, route to the right tool based on user intent:
| User Intent | Tool Sequence | Agent Responsibility |
|---|---|---|
| "Read/open/show me X" | resolve → read_document | Present full text |
| "Summarize X" | resolve → read_document | Summarize content (LLM capability) |
| "Find/search for Y in X" | resolve → search_document | Show search results with context |
| "What's in X" / "Describe X" | resolve → read_document | High-level description (LLM capability) |
| "How large is X" / "When was X modified" | resolve → get_document_metadata | Extract and present metadata |
| "What docs are on my desktop" | list_documents | No resolution needed; direct listing |
| "Create a diagram from X" | resolve → read_document | Parse content, generate diagram (LLM capability) |
| "Extract X from Y" (e.g., table data) | resolve → read_document | Parse and reformat (LLM capability) |
If resolve_document returns status: "ambiguous":
{
status: "ambiguous",
candidates: ["/path/to/report.docx", "/path/to/report_v2.docx"],
message: "Multiple matches found..."
}
Agent action:
resolve_document again with more specific location or name hintExample:
Found 2 documents matching "report":
1. /Users/me/Desktop/report.docx (modified 2 days ago)
2. /Users/me/Downloads/report_final.docx (modified 1 hour ago)
Which one would you like me to read?
If resolve_document returns status: "not_found":
Agent action:
User: "Read the meeting notes on my desktop"
Agent workflow:
1. resolve_document(name="meeting notes", location="desktop")
→ { status: "found", resolved_path: "/Users/me/Desktop/meeting notes.docx" }
2. read_document(path="/Users/me/Desktop/meeting notes.docx")
→ Returns full text
3. Present text to user with formatting
User: "Search for 'Q1 budget' in the finance report I downloaded"
Agent workflow:
1. Recognize intent: search + location hint (downloads)
2. resolve_document(name="finance report", location="downloads")
→ { status: "found", resolved_path: "/Users/me/Downloads/finance_report.docx" }
3. search_document(path="/Users/me/Downloads/finance_report.docx", query="Q1 budget")
→ Returns matching lines with line numbers
4. Present results: "Found 3 matches..."
User: "Summarize the status report"
Agent workflow:
1. resolve_document(name="status report", location=undefined)
→ { status: "ambiguous", candidates: [
"/Users/me/Desktop/status_report_2024.docx",
"/Users/me/Downloads/status_report_draft.docx"
]}
2. Ask user: "I found 2 documents. Which one?"
- Option A: /Desktop/status_report_2024.docx
- Option B: /Downloads/status_report_draft.docx
3. User picks A
4. read_document(path="/Users/me/Desktop/status_report_2024.docx")
→ Returns text
5. Agent summarizes
User: "When was the architecture document last modified?"
Agent workflow:
1. resolve_document(name="architecture document", location=undefined)
→ { status: "found", resolved_path: "/Users/me/Documents/architecture.docx" }
2. get_document_metadata(path="/Users/me/Documents/architecture.docx")
→ { modifiedAt: "2026-03-10T14:22:00Z", ... }
3. Present: "Last modified on March 10, 2026 at 2:22 PM"
User: "Read /etc/docs/my_file.docx"
Agent workflow:
1. Recognize: user provided absolute path
2. Skip resolve_document
3. read_document(path="/etc/docs/my_file.docx") directly
❌ Calling read_document with a friendly name
// DON'T DO THIS
read_document(path="foo") // Will fail — "foo" is not a valid path
// DO THIS INSTEAD
resolve_document(name="foo") → read_document(path=resolved_path)
❌ Ignoring ambiguous matches
// DON'T DO THIS — silently pick first candidate
if (ambiguous) { use candidates[0] }
// DO THIS INSTEAD
if (ambiguous) { ask user to clarify }
❌ Not extracting location hints from user language
// DON'T DO THIS
resolve_document(name="budget report") // omits location hint even though user said "on my desktop"
// DO THIS INSTEAD
resolve_document(name="budget report", location="desktop")
❌ Calling list_documents without a clear purpose
// DON'T DO THIS — user didn't ask for a listing
resolve_document(name="X") fails → list all files on system
// DO THIS INSTEAD
If user wants to see available files, call list_documents with a specific location.
If resolve fails, offer to list that location.
❌ Chaining tools without waiting for resolution
// DON'T DO THIS — spawning all tools at once
resolve_document(...)
read_document(...) // May use wrong path if resolve is still pending
search_document(...)
// DO THIS INSTEAD
Wait for resolve_document result.
Then call the appropriate tool (read OR search OR metadata).
When handling a document request:
resolve_documentresolve_document