Research Skill

Description

Conduct open-ended research on a topic, building a living markdown document. The conversation is ephemeral; the document is what matters.

Trigger

Activate when the user wants to:

Research a topic, idea, or question
Explore something before committing to building it
Investigate options, patterns, or approaches
Create a "research doc" or "investigation"
Run deep async research on a complex topic

Research Directory

Each research topic gets its own folder:

~/.openclaw/workspace/research/<topic-slug>/
├── prompt.md          # Original research question/prompt
├── research.md        # Main findings (Parallel output or interactive notes)
├── research.pdf       # PDF export (when generated)
└── ...                # Any other related files (data, images, etc.)

Two Research Modes

1. Interactive Research (default)

For topics you explore together in conversation. You search, synthesize, and update the doc in real-time.

2. Deep Research (async)

For complex topics that need comprehensive investigation. Uses the Parallel AI API via parallel-research CLI. Takes minutes to hours, returns detailed markdown reports.

When to use deep research:

Market analysis, competitive landscape
Technical deep-dives requiring extensive source gathering
Multi-faceted questions that benefit from parallel exploration
When user says "deep research" or wants comprehensive coverage

Interactive Research Workflow

1. Initialize Research

Create the research folder at ~/.openclaw/workspace/research/<topic-slug>/

Create prompt.md with the original question:

# <Topic Title>

> <The core question or curiosity>

**Started:** <date>

Create research.md with the working structure:

# <Topic Title>

**Status:** Active Research
**Started:** <date>
**Last Updated:** <date>

---

## Open Questions
- <initial questions to explore>

## Findings
<!-- Populated as we research -->

## Options / Approaches
<!-- If comparing solutions -->

## Resources
<!-- Links, references, sources -->

## Next Steps
<!-- What to explore next, or "graduate to project" -->

Confirm with user - Show the folder was created and ask what to explore first.

2. Research Loop

For each exchange:

Do the research - Web search, fetch docs, explore code
Update the document - Add findings, move answered questions, add sources
Show progress - Note what was added (don't repeat everything)
Prompt next direction - End with a question or suggestion

Key behaviors:

Update existing sections over creating new ones
Use bullet points for findings; prose for summaries
Note uncertainty ("seems like", "according to X", "unverified")
Link to sources whenever possible

3. Synthesis Checkpoints

Every 5-10 exchanges, offer to:

Write a "Current Understanding" summary
Prune redundant findings
Reorganize if unwieldy
Check blind spots

4. Completion

When research is complete, update the status in research.md:

"Status: Complete" — Done, stays in place as reference
"Status: Ongoing" — Living doc, will be updated over time

If the research is specifically for building a project:

Graduate to ~/specs/<project-name>.md as a project spec
Or create a project directly based on findings
Update status to "Status: Graduated → ~/specs/..."

Most research is just research — it doesn't need to become a spec. Only graduate if you're actually building something from it.

Deep Research Workflow

1. Start Deep Research

parallel-research create "Your research question" --processor ultra --wait

Processor options:

lite, base, core, pro, ultra (default), ultra2x, ultra4x, ultra8x
Add -fast suffix for speed over depth: ultra-fast, pro-fast, etc.

Options:

-w, --wait — Wait for completion and show result
-p, --processor — Choose processor tier
-j, --json — Raw JSON output

2. Schedule Auto-Check (optional)

Deep research tasks take minutes to hours. You'll want to poll for results automatically rather than checking manually.

Options:

OpenClaw users: See OPENCLAW.md for cron-based auto-check scheduling
Other setups: Use any scheduler (cron, systemd timer, CI job) to periodically run parallel-research status <run_id> and parallel-research result <run_id> until complete
Simple approach: Just use parallel-research create "..." --wait to block until done (works for shorter tasks)

3. Manual Check (if needed)

parallel-research status <run_id>
parallel-research result <run_id>

4. Save to Research Folder

Create the research folder and save results:

~/.openclaw/workspace/research/<topic-slug>/
├── prompt.md          # Original question + run metadata
├── research.md        # Full Parallel output

prompt.md should include:

# <Topic Title>

> <Original research question>

**Run ID:** <run_id>
**Processor:** <processor>
**Started:** <date>
**Completed:** <date>

research.md contains the full Parallel output, plus any follow-up notes.

PDF Export

All PDFs go in the research folder — never save to tmp/. Whether using export-pdf, the browser pdf action, or any other method, the output path must be research/<topic-slug>/.

Use the export-pdf script to convert research docs to PDF:

export-pdf ~/.openclaw/workspace/research/<topic-slug>/research.md
# Creates: ~/.openclaw/workspace/research/<topic-slug>/research.pdf

For browser-generated PDFs (e.g. saving a webpage as PDF):

browser pdf → save to research/<topic-slug>/<descriptive-name>.pdf

Note: Tables render as stacked rows (PyMuPDF limitation). Acceptable for research docs.

Commands

"new research: " - Start interactive research doc
"deep research: " - Start async deep research
"show doc" / "show research" - Display current research file
"summarize" - Synthesis checkpoint
"graduate" - Move research to next phase
"archive" - Mark as complete reference
"export pdf" - Export to PDF
"check research" - Check status of pending deep research tasks

Document Principles

Atomic findings - One insight per bullet
Link everything - Sources, docs, repos
Capture context - Why did we look at this?
Note confidence - Use qualifiers when uncertain
Date important findings - Especially for fast-moving topics

Setup

See SETUP.md for first-time installation of:

parallel-research CLI
PDF export tools (pandoc, PyMuPDF)

research