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npx skills add tavily-ai/skills --skill tavily-research -a claude-code -yUse this when the answer has to be built from many sources. A single fact or
answer to find is a search: follow tavily-search instead.
Search and read pages as tavily-search describes. Load it only if it isn't
loaded yet.
Ask when a term has two meanings, the user assumed a place, or a name is two different entities. Otherwise start.
Split into subtopics that do not overlap and that together cover the question. Carry the user's limits with every subtopic: dates, places, and what is out of scope. Use 3 subtopics when you are unsure, 4 for a comparison with separate criteria, 5 for separate entities, regions or domains, and more only for a large set.
With subagents: choose a title of 3 to 6 words, create
research_notes/{title}/ and reports/ in the working directory, and start
one general-purpose subagent per subtopic in the same turn. Give each the
subtopic, the key questions, the user's limits, the absolute path of its notes
file, and this first step: read references/researcher.md at its absolute path
next to this skill.
On your own: run each subtopic's searches in parallel, as tavily-search
describes, and extract the main sources for each. Keep the findings and their
URLs in your context. Don't write notes files.
Before writing, run another round for any part of the question that would leave its section thin.
Follow references/report-writer.md. On your own, write it once, as
your reply. Save it to reports/{title}.md only when the user asked for a
file, and then give the path after the report. With subagents, have one agent
write reports/{title}.md from the notes, then give the user the full report
in your reply, followed by its path.
If this conversation already produced a report on the subject, build on it: research only what is new or needs checking again.
---
name: tavily-research
description: |
Research a topic in depth with Tavily. Use this skill when a question needs many sources gathered and weighed together: analysing a market, policy, technology or trend, comparing options across several criteria, reviewing the literature, or any request to research, investigate or analyze something in depth. A single fact or answer to find, even one with many clues, is a tavily-search task. For one CRM record use tavily-entity, for a table of matches use tavily-list, and for a recurring check use tavily-monitor.
allowed-tools: Bash(tvly *)
---
# Tavily research
Use this when the answer has to be built from many sources. A single fact or
answer to find is a search: follow `tavily-search` instead.
Search and read pages as `tavily-search` describes. Load it only if it isn't
loaded yet.
## Steps
### 1. Ask only when the answer would change the research
Ask when a term has two meanings, the user assumed a place, or a name is two
different entities. Otherwise start.
### 2. Split the question
Split into subtopics that do not overlap and that together cover the question.
Carry the user's limits with every subtopic: dates, places, and what is out of
scope. Use 3 subtopics when you are unsure, 4 for a comparison with separate
criteria, 5 for separate entities, regions or domains, and more only for a
large set.
### 3. Research the subtopics together
**With subagents:** choose a title of 3 to 6 words, create
`research_notes/{title}/` and `reports/` in the working directory, and start
one general-purpose subagent per subtopic in the same turn. Give each the
subtopic, the key questions, the user's limits, the absolute path of its notes
file, and this first step: read `references/researcher.md` at its absolute path
next to this skill.
**On your own:** run each subtopic's searches in parallel, as `tavily-search`
describes, and extract the main sources for each. Keep the findings and their
URLs in your context. Don't write notes files.
### 4. Fill thin parts, then write
Before writing, run another round for any part of the question that would
leave its section thin.
### 5. Write and deliver the answer
Follow `references/report-writer.md`. On your own, write it once, as
your reply. Save it to `reports/{title}.md` only when the user asked for a
file, and then give the path after the report. With subagents, have one agent
write `reports/{title}.md` from the notes, then give the user the full report
in your reply, followed by its path.
If this conversation already produced a report on the subject, build on it:
research only what is new or needs checking again.