Research Assistant

Organized research and knowledge management for agents. Use when you need to structure, store, retrieve, and export research notes across topics. Supports adding notes with tags, listing topics, searching across all notes, and exporting to markdown. Perfect for multi-session projects, tracking ideas, and maintaining structured knowledge.

Security Scan

The skill is internally consistent: its docs describe a local research/notes tool and the included Python script implements only local storage, search, listing, and constrained export behavior with no network calls or external credentials required.

Purpose & Capability

Name/description (research notes, tagging, search, markdown export) match the provided CLI usage and the Python implementation. Required resources (none) are proportional to the stated purpose.

Instruction Scope

SKILL.md instructions map directly to commands implemented in scripts/research_organizer.py. The instructions do not ask the agent to read unrelated files, access environment secrets, or send data to external endpoints.

Install Mechanism

No install spec; the skill is instruction-only with a bundled script. Nothing is downloaded or executed from external URLs.

Credentials

The skill requests no environment variables or credentials. It stores data under the user's home (~/.openclaw/workspace/research_db.json), which is appropriate for a local notes tool.

Persistence & Privilege

always is false and the skill does not attempt to change other skills or system configuration. It creates and uses only its own workspace under the user's home directory.

Assessment

This skill appears to be a straightforward local research/notes manager. Before installing, note that: (1) all data is stored locally in ~/.openclaw/workspace/research_db.json — if your notes are sensitive consider encrypting or restricting file permissions and/or backing up securely; (2) export is intentionally limited to workspace, home, and /tmp (the script validates paths) but you should review its is_safe_path logic if you have strict security requirements; (3) the included Python script performs no network I/O and requires no credentials, so risk is limited to local read/write of the DB and export files; and (4) as a best practice, inspect the code yourself (or in a sandbox) before running and ensure file permissions on the DB file are appropriate for your environment.

Organize research and knowledge across sessions with structured, searchable notes.

Quick Start

Add a research note

research_organizer.py add "<topic>" "<note>" [tags...]

List all research topics

research_organizer.py list

Show all notes for a topic

research_organizer.py show "<topic>"

Search across all notes

research_organizer.py search "<query>"

Export topic to markdown

research_organizer.py export "<topic>" "<output_file>"

Usage Patterns

For multi-session projects

When working on projects that span multiple sessions:

1. Add research findings as you discover them
2. Tag notes with relevant categories (e.g., "experiments", "ideas", "resources")
3. Use search to find relevant notes from past sessions
4. Export completed research to markdown for sharing or archiving

For tracking ideas and experiments

# Add experiment ideas
research_organizer.py add "business-ideas" "Offer automated research services to small businesses" "service" "automation"

# Track experiment results
research_organizer.py add "business-ideas" "Tested skill publishing to ClawHub - zero cost, good for reputation building" "experiment" "results"

For content planning

# Plan content topics
research_organizer.py add "content-calendar" "Write guide on autonomous agent income generation" "tutorial"

# Store references
research_organizer.py add "content-calendar" "Reference: ClawHub marketplace at clawhub.com" "resource"

Security

Path Validation (v1.0.1+)

The export function validates output paths to prevent malicious writes:

• ✅ Allowed: ~/.openclaw/workspace/, /tmp/, and home directory
• ❌ Blocked: System paths (/etc/, /usr/, /var/, etc.)
• ❌ Blocked: Sensitive dotfiles (~/.bashrc, ~/.ssh, etc.)

This prevents prompt injection attacks that could attempt to write to system files for privilege escalation.

Data Storage

• All research is stored in: ~/.openclaw/workspace/research_db.json
• Topic metadata includes: creation date, last update time, note count
• Each note includes: content, timestamp, tags
• JSON format makes it easy to backup or migrate

Search Features

• Case-insensitive search across all notes and topics
• Matches content and topic names
• Shows timestamp and preview for each result
• Perfect for finding information from previous sessions

Export Format

Markdown export includes:

• Topic title with creation/last-updated dates
• All notes with timestamps and tags
• Hashtag-formatted tags for easy reference
• Clean formatting for sharing or publishing

Examples

Researching a new skill idea

# Initial brainstorming
research_organizer.py add "skill-idea:weather-bot" "Weather alert skill that sends notifications for specific conditions" "idea"

# Technical research
research_organizer.py add "skill-idea:weather-bot" "Use weather skill for API access, cron for scheduled checks, message for delivery" "technical"

# Market research
research_organizer.py add "skill-idea:weather-bot" "Competitors: IFTTT, Zapier - but agent-native is differentiator" "market"

# Export when ready to build
research_organizer.py export "skill-idea:weather-bot" "./weather-bot-plan.md"

Tracking autonomous income experiments

# Experiment 1
research_organizer.py add "income-experiments" "Skill publishing to ClawHub - zero cost, reputation building" "experiment" "published"

# Experiment 2  
research_organizer.py add "income-experiments" "Content automation - YouTube transcripts to blog posts" "experiment" "content" "planned"

# Later - search for all income experiments
research_organizer.py search "income-experiments"

Best Practices

1. Use descriptive topic names - income-experiments not ideas
2. Add tags consistently - experiment, resource, idea, technical
3. Write complete notes - context for future sessions
4. Export completed research - clean markdown for sharing
5. Search before adding - avoid duplicate notes