parallel-ai-researchConduct open-ended research on a topic, building a living markdown document. Supports interactive and deep research modes.
Install via ClawdBot CLI:
clawdbot install BrennerSpear/parallel-ai-researchConduct open-ended research on a topic, building a living markdown document. The conversation is ephemeral; the document is what matters.
Activate when the user wants to:
Each research topic gets its own folder:
~/.openclaw/workspace/research/<topic-slug>/
βββ prompt.md # Original research question/prompt
βββ research.md # Main findings (Parallel output or interactive notes)
βββ research.pdf # PDF export (when generated)
βββ ... # Any other related files (data, images, etc.)
For topics you explore together in conversation. You search, synthesize, and update the doc in real-time.
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:
~/.openclaw/workspace/research//
# <Topic Title>
> <The core question or curiosity>
**Started:** <date>
# <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" -->
For each exchange:
Key behaviors:
Every 5-10 exchanges, offer to:
When research is complete, update the status in research.md:
If the research is specifically for building a project:
~/specs/.md as a project specMost research is just research β it doesn't need to become a spec. Only graduate if you're actually building something from it.
parallel-research create "Your research question" --processor ultra --wait
Processor options:
lite, base, core, pro, ultra (default), ultra2x, ultra4x, ultra8x-fast suffix for speed over depth: ultra-fast, pro-fast, etc.Options:
-w, --wait β Wait for completion and show result-p, --processor β Choose processor tier-j, --json β Raw JSON outputDeep research tasks take minutes to hours. You'll want to poll for results automatically rather than checking manually.
Options:
OPENCLAW.md for cron-based auto-check schedulingparallel-research status and parallel-research result until completeparallel-research create "..." --wait to block until done (works for shorter tasks)parallel-research status <run_id>
parallel-research result <run_id>
Create the research folder and save results:
~/.openclaw/workspace/research/<topic-slug>/
βββ prompt.md # Original question + run metadata
βββ 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.
All PDFs go in the research folder β never save to tmp/. Whether using export-pdf, the browser pdf action, or any other method, the output path must be research/.
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 β save to research/<topic-slug>/<descriptive-name>.pdf
Note: Tables render as stacked rows (PyMuPDF limitation). Acceptable for research docs.
See SETUP.md for first-time installation of:
parallel-research CLIGenerated Mar 1, 2026
A startup planning to launch a new SaaS product uses deep research to analyze competitors, market size, and pricing models. The interactive mode helps refine initial questions and document findings in a structured markdown file for team review.
A graduate student employs interactive research to explore recent studies on a specific topic, updating a living document with sources and summaries. Deep research can be used later for comprehensive analysis of trends and gaps in the literature.
A product manager investigates technical approaches and user needs for a new feature, using interactive research to gather options and document findings. The research folder helps track progress and can graduate to a project spec if development proceeds.
A marketing team uses deep research to gather data on competitor strategies and industry benchmarks, saving results as PDFs for presentations. Interactive mode allows real-time updates and synthesis checkpoints to refine campaign direction.
A compliance officer researches new regulations affecting their industry, using interactive research to document requirements and sources. Deep research can provide comprehensive reports on complex legal landscapes for internal audits.
Offer tiered access to deep research reports and interactive tools for businesses, charging monthly fees based on processor tiers like ultra or pro. Revenue comes from recurring subscriptions and premium features like PDF exports.
Provide tailored research services for clients in specific industries, using the skill to generate detailed markdown documents and PDFs. Revenue is generated through project-based fees and ongoing support contracts.
Offer a free version with basic interactive research features and charge for advanced deep research modes, higher processor tiers, and automated scheduling. Revenue streams include pay-per-use credits and premium upgrades.
π¬ Integration Tip
Integrate with existing project management tools by exporting research.md files to shared repositories, and use cron jobs for auto-checking deep research results to streamline workflows.
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