Deep-dive research on any topic. Triggers when the user says "research [topic]", "look into [topic]", "find out about [topic]", "what do you know about [topic]", "investigate [topic]", "I need information on [topic]", "tell me about [topic]", "dig into [topic]", "analyze [topic]", "explore [topic]", or any request for structured information gathering, analysis, or background research on a subject. Also triggers for "compare [X] vs [Y]", "pros and cons of [topic]", or "should I choose [X] or [Y]". Do NOT use for ongoing competitor monitoring or watchlist updates (use competitor-watch), morning briefings or daily news digests (use daily-briefing), quick one-answer factual lookups that need no multi-source synthesis, or producing polished formatted research reports (use report-writer — topic-research produces raw synthesis, report-writer formats it into a document).
From tandemnpx claudepluginhub binatrixai/tandem-marketplace --plugin tandemThis skill is limited to using the following tools:
evals/evals.jsonexamples/sample-research.mdtemplate.mdExecutes pre-written implementation plans: critically reviews, follows bite-sized steps exactly, runs verifications, tracks progress with checkpoints, uses git worktrees, stops on blockers.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Deep-dive research skill that produces structured, actionable research outputs
at three depth levels. All outputs follow the format defined in template.md.
For a complete example of detailed-level research, see examples/sample-research.md.
See METHODOLOGY.md language mirror rule. Reply in the user's language.
Extract the research topic from the user's message. If the topic is unclear or too broad, clarify using AskUserQuestion:
Your topic seems broad. Want me to narrow it down?
AskUserQuestion:
- "[Narrower angle A]"
- "[Narrower angle B]"
- "Keep it broad — cover the full topic"
Present depth options via AskUserQuestion:
How deep should I go on this research?
AskUserQuestion:
- "Quick overview — 1-2 paragraphs, key points only"
- "Detailed analysis — structured sections with findings"
- "Comprehensive report — full report with citations and recommendations"
Depth definitions:
Gather information using available tools and knowledge:
Structure findings according to the selected depth level using template.md.
Deliver the research output formatted per template.md for the chosen depth.
Always include at the end:
After presenting research, offer save options via AskUserQuestion:
Research complete. What would you like to do with it?
AskUserQuestion:
- "Save to research folder"
- "Save and create a follow-up task"
- "Don't save — just needed the info"
If "Save to research folder":
~/Tandem/research/[topic-slug]-[YYYY-MM-DD].mdIf "Save and create a follow-up task":
What's the follow-up task?
AskUserQuestion:
- "Review and make a decision by [date]"
- "Share with team / stakeholder"
- "Do deeper research on a specific finding"
- "Custom task — let me describe it"
~/Tandem/tasks/MEMORY.md via the task-manager skillWhen the user asks to compare options (e.g., "X vs Y", "pros and cons of Z"), use the comparison variant:
After completing research, suggest 1-2 next steps:
AskUserQuestion:
- "Deep-dive into [specific finding that deserves more attention]"
- "Create an action plan based on these findings"
- "Nothing else for now"
If the research revealed competitors or market dynamics:
AskUserQuestion:
- "Set up competitor tracking for [identified competitors]"
- "Schedule a weekly update on this topic"
- "Nothing else for now"
After completing the workflow, append an entry to ~/Tandem/stats.json:
{
"type": "research",
"action": "completed",
"count": 1,
"timeSavedMinutes": 45,
"description": "Research completed: AI market trends 2026",
"timestamp": "<current ISO 8601>"
}
If ~/Tandem/stats.json does not exist, create it as [<entry>]. If it exists, read it, parse the JSON array, append the new entry, and write it back.
After appending to stats.json, follow the /sync workflow from tandem-skills/core/sync/SKILL.md to rebuild ~/Tandem/dashboard.html with updated statistics. This keeps the dashboard current after every skill run. If /sync fails (e.g., dashboard.html does not exist yet), continue — the main skill workflow must complete successfully regardless of sync outcome.