| name | deep-scientific-research |
| description | Deep scientific research pipeline with subagent orchestration, parallel web search, and citation management. Use this skill whenever the user asks for a literature review, scientific research summary, evidence synthesis, systematic review, or any deep research task that requires searching multiple sources and producing a cited report. Also triggers on phrases like "research this topic", "find papers on", "what does the evidence say about", "literature review on", or "deep dive into".
|
Deep Scientific Research Skill
A multi-agent pipeline for conducting rigorous scientific research using
the Claude Agent SDK. The system breaks a research question into focused
subtopics, spawns parallel researcher subagents to search the web, then
synthesizes everything into a unified report with a numbered citation list.
Architecture
User Question
|
v
+-------------------+
| Orchestrator | Plans subtopics, coordinates agents
| (Lead Agent) |
+---------+---------+
| spawns 3-6 in parallel
+-----+-----+-----+
v v v v
+------+------+------+
|Rsrch1||Rsrch2||Rsrch3| Each searches web, returns
| || || | structured findings + URLs
+--+---++--+---++--+---+
| | |
+-------+-------+
v
+---------------+
| Synthesizer | Merges, deduplicates, renumbers
| Subagent | citations, writes final report
+-------+-------+
v
Final Report
(Markdown + References)
Subagent Definitions
This skill relies on two subagents that should be available in the project:
researcher
- Tools:
WebSearch, WebFetch
- Model:
sonnet (fast, cost-effective for search tasks)
- Purpose: Searches the web for a specific subtopic. Returns
structured findings with source URLs.
- Output format: Markdown with
## Subtopic, ### Findings,
### Sources sections.
synthesizer
- Tools: None (pure text synthesis)
- Model:
sonnet
- Purpose: Takes all researcher outputs and produces a unified,
well-structured report with globally renumbered citations.
- Output format: Full research report with Executive Summary,
numbered sections, Open Questions, and References list.
Workflow
When the user asks a research question:
-
PLAN - Break the research question into 3-6 focused subtopics.
Each subtopic should be a specific, searchable angle of the question.
-
DELEGATE - For every subtopic, invoke the "researcher" subagent with a
clear, precise prompt. Include the subtopic title and 2-3 specific
search queries the researcher should try. Spawn researchers in PARALLEL
whenever possible to save time.
-
SYNTHESIZE - Once all researchers report back, combine findings into a
single, coherent research report using the "synthesizer" subagent.
Pass ALL researcher outputs to the synthesizer verbatim.
-
DELIVER - Present the synthesizer's final report to the user.
Save the report to out/report_<timestamp>.md.
Important Rules
- Always use the researcher subagent for gathering information. Never
search yourself.
- Always use the synthesizer subagent for the final report. Never write
the report yourself.
- When calling a subagent, pass all necessary context in the prompt
string - subagents cannot see this conversation.
- If a researcher returns thin results, you may spawn a follow-up
researcher with refined queries.
- Your final message to the user should be the synthesized report,
presented verbatim without modification.
Customization
Domain-specific research
The researcher subagent can be tuned to prioritize domain-specific databases:
- Biomedical: PubMed, ClinicalTrials.gov, bioRxiv
- Physics/Math: arXiv, APS journals
- Computer Science: Semantic Scholar, ACM DL, DBLP
- Legal: case law databases, government registers
- Economics: NBER, SSRN, Fed publications
Cost Expectations
A typical research query spawns 3-6 researcher subagents, each making
3-5 web searches. Expect roughly:
- Simple topic: ~$0.50-1.00 (3 researchers, ~15 searches)
- Complex topic: ~$2.00-5.00 (6 researchers + follow-ups, ~30 searches)
