TXTWRK — SEARCH LOOK ALIKE
Checklist Feature Development Report
Date: 3 November 2026
Project: TXTWRK
Feature: Search Look Alike
Status: Proposed Development
Category: Checklist Technology / Search / Community Intelligence
A post announcement!
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1. FEATURE OVERVIEW
Search Look Alike is an intelligent discussion-discovery feature designed to help people find the most relevant place for their contributions before publishing.
Rather than creating another disconnected post, TXTWRK will suggest existing conversations, checklist items, or alternative checklists where the contribution could belong.
Core Principle
Find the right conversation, extend existing knowledge, and reduce unnecessary duplication.
This feature builds upon TXTWRK's existing QueryMember search infrastructure and checklist technology.
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2. THE USER EXPERIENCE
Example Scenario
A user opens their Web Development Checklist and begins writing:
> We should improve how our community handles startup funding and investment opportunities.
Before publishing, the user can activate:
Search Look Alike
The system examines the draft and searches for related discussions.
Example Suggested Results
1. Startup Investment Opportunities
•Location: Business Checklist
•Example relevance: 94%
2. Community Funding Ideas
•Location: Community Checklist
•Example relevance: 86%
3. Website Funding Page
•Location: Web Development Checklist
•Example relevance: 71%
These are illustrative examples, not actual TXTWRK search results.
Available Actions
Users can:
•Extend an existing discussion.
•Reply directly to a relevant comment.
•Select a different checklist.
•Continue writing their original post.
•Publish independently.
•Adjust the search scope.
•Review related topics without losing their draft.
The user always retains control over where their contribution is published.
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3. SEARCH SCOPE AND FILTERS
Search Look Alike should support multiple search boundaries.
Search Scope Options
Current Checklist
Search only within the checklist currently being viewed.
All User Checklists
Search across the selected user's accessible checklists.
Selected Checklist
Manually select another checklist to search.
Entire Network
Search across publicly accessible TXTWRK content or other content the user has permission to access.
Additional Filters
Potential filters include:
•Username
•Checklist
•Checklist item
•Post
•Comment
•Reply
•Topic
•Keyword
•Date
•Content type
•Relevance
These filters build upon TXTWRK's existing QueryMember search concepts.
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4. FUZZY SEARCH AND KEYWORD MATCHING
The first implementation should use lightweight text-processing methods.
Keyword Extraction
Identify important terms within the user's draft.
Example:
"Improving startup investment opportunities for local communities."
Possible keywords:
•Startup
•Investment
•Funding
•Community
•Business
Fuzzy Matching
Recognize similar terms and variations.
Examples:
•Startup / Start-up
•Investment / Investing
•Community / Communities
•Funding / Finance
•Development / Developing
Related Keyword Groups
TXTWRK could maintain lightweight keyword relationships.
Example:
Automotive
•Car
•Vehicle
•Engine
•Motor
•Transport
Business
•Startup
•Investment
•Funding
•Shares
•Marketplace
Web Development
•Website
•Server
•API
•JavaScript
•Framework
These relationships could improve search results without requiring an AI model for every query.
Local Caching
Frequently used keyword relationships and search results may be cached to reduce repeated processing.
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5. PROPOSED TECHNICAL WORKFLOW
Step 1 — Capture Draft
The user writes a contribution inside the TXTWRK post box.
Step 2 — Analyze Text
The system normalizes the text and identifies meaningful keywords.
Step 3 — Search Existing Content
Use existing QueryMember-compatible search infrastructure to retrieve related discussions within the selected scope.
Step 4 — Rank Matches
Evaluate candidate results using:
•Keyword overlap
•Fuzzy similarity
•Topic relevance
•Checklist context
•Content type
•Discussion relevance
Step 5 — Present Suggestions
Display the most relevant conversations inside a lightweight overlay.
Step 6 — User Selection
The user chooses whether to:
•Extend an existing conversation.
•Redirect the contribution.
•Change the search scope.
•Continue with a new post.
Step 7 — Preserve the Draft
The original contribution must remain intact throughout the process.
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6. POST BOX INTEGRATION
Search Look Alike should be available directly inside the existing TXTWRK post box.
Proposed Interface
Post Box
Write your contribution...
Search Look Alike
Search Scope
•Current Checklist
•All User Checklists
•Selected Checklist
•Entire Network
Suggested Discussions
1. Related discussion
2. Related checklist item
3. Related comment
Available Actions
•Extend Here
•View Discussion
•Change Checklist
•Publish New Post
Automatic Suggestions
The feature may optionally suggest related conversations while the user is drafting.
To minimize unnecessary processing, automatic searches should use:
•Input debouncing
•Minimum text thresholds
•Limited result counts
•Cached results
•Efficient database indexes
Automatic suggestions should not interrupt typing.
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7. CHECKLIST OVERLAY INTEGRATION
Search Look Alike should also be available within TXTWRK checklist overlays.
This allows users to discover related discussions without navigating away from their current workspace.
Benefits
•Faster navigation
•Reduced duplicate discussions
•Better checklist organization
•Improved community collaboration
•Greater visibility of existing knowledge
•More productive contributions
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8. CONNECTION WITH QUERYMEMBER
QueryMember is an existing TXTWRK search capability described as supporting searches across checklist and network boundaries.
Search Look Alike can build upon this infrastructure.
QueryMember
Purpose: Find information.
Users search for posts, notes, discussions, and other relevant content.
Search Look Alike
Purpose: Find where a contribution belongs.
The system analyzes a draft and recommends relevant destinations.
Combined Experience
QueryMember helps users discover existing knowledge.
Search Look Alike helps users extend that knowledge.
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9. CONNECTION WITH ALL ACTIVITY
TXTWRK's All Activity feature provides visibility into interactions occurring within a checklist.
These may include:
•Posts
•Comments
•Replies
•Likes
•Checklist interactions
•Other recorded activity
Combined Workflow
QueryMember
Discover information.
All Activity
Understand what is happening.
Search Look Alike
Find where to contribute.
Together, these capabilities support organized and continuously evolving community knowledge spaces.
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10. PERFORMANCE AND SCALABILITY
The system should remain efficient as checklist activity grows.
Initial Implementation
Use:
•Existing database search capabilities
•Indexed text fields
•Lightweight keyword extraction
•Fuzzy matching
•Limited candidate retrieval
•Query caching
Future Improvements
Potential enhancements include:
•Full-text search indexes
•Advanced relevance ranking
•Semantic search
•Vector embeddings
•AI-assisted topic classification
•Personalized search suggestions
Important Consideration
Text-only processing does not automatically guarantee low computational cost.
Search performance depends on:
•Database size
•Query complexity
•Index availability
•Search frequency
•Concurrent users
•Ranking methods
TXTWRK should measure actual performance before introducing more computationally expensive features.
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11. SECURITY AND PERMISSIONS
Search Look Alike must respect existing TXTWRK access permissions.
Requirements
•Do not reveal private checklist content.
•Do not expose restricted discussions.
•Apply permission checks before displaying results.
•Validate all user-supplied search inputs.
•Preserve drafts securely.
•Prevent unauthorized cross-checklist access.
•Apply appropriate query limits and rate controls.
Public content may be discoverable across the network.
Private content must remain restricted to authorized users.
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12. DEVELOPMENT CHECKLIST
Phase 1 — Core Feature
• Connect Search Look Alike to the post box.
• Capture draft text for matching.
• Implement keyword extraction.
• Connect existing QueryMember search infrastructure.
• Return related discussions.
• Display suggestions in an overlay.
Phase 2 — Navigation
• Add Current Checklist filter.
• Add All User Checklists filter.
• Add Selected Checklist filter.
• Add permission-aware Network Search.
• Allow users to select existing discussions.
• Support direct replies.
• Preserve the original draft.
Phase 3 — Optimization
• Introduce fuzzy keyword matching.
• Add relevance ranking.
• Implement query caching.
• Optimize database indexes.
• Introduce automatic suggestions.
• Monitor search performance.
Phase 4 — Future Intelligence
• Evaluate semantic matching.
• Explore AI-assisted topic classification.
• Improve cross-checklist recommendations.
• Measure suggestion accuracy.
• Evaluate user engagement and contribution placement.
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13. SUCCESS MEASURES
TXTWRK can evaluate the feature through:
Suggestion Accuracy
How often do users select a recommended discussion?
Discussion Reuse
Are more users extending existing conversations?
Search Performance
How quickly are suggestions returned?
Contribution Placement
Are contributions being published in more relevant locations?
User Experience
Does the feature make posting easier?
Community Knowledge
Are related discussions becoming easier to discover and develop?
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14. WHAT MAKES THIS FEATURE VALUABLE?
Traditional search helps people find information.
Search Look Alike introduces a contribution-focused experience.
Instead of simply asking:
"Has somebody already discussed this?"
TXTWRK helps answer:
"Where would my contribution be most useful?"
That distinction supports the wider TXTWRK vision of making community work more discoverable, organized, collaborative, and accessible.
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15. RECOMMENDED NEXT MILESTONE
Build an initial Search Look Alike prototype using TXTWRK's existing search infrastructure.
Prioritize:
1. Keyword extraction.
2. Permission-aware checklist search.
3. Ranked discussion suggestions.
4. Draft preservation.
5. Direct navigation to existing conversations.
Evaluate the results before introducing heavier AI processing.
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FINAL SUMMARY
TXTWRK — Search Look Alike
A proposed checklist intelligence feature that helps people discover related conversations and place their contributions where they can create the greatest value.
By connecting existing QueryMember capabilities, checklist organization, and All Activity visibility, TXTWRK can help communities build upon existing knowledge instead of repeatedly starting from scratch.
Find the conversation.
Extend the knowledge.
Strengthen the community.
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TXTWRK
https://www.txtwrk.com
Development specification based on the feature discussion of 3 November 2026. Implementation and testing status remain to be verified.
COMMUNITY
People