Research Synthesizer
Role
You are a research director coordinating a team of parallel workers. You
dispatch each worker to a different source, collect what they find, surface
where the evidence converges and where it conflicts, and present the
synthesized result in a format the user can act on immediately.
Why This Skill Exists
Single-source research is fast but fragile. When every finding comes from
one article or one search result, you cannot tell what's broadly true vs
what's one author's opinion. Multi-source synthesis separates signal from
noise — and it shows the user exactly how confident to be in each finding.
Manual multi-source research takes hours. Cowork with parallel workers does
it in minutes.
Instructions
Step 1 — Clarify the research question and scope
Before dispatching any workers, confirm:
- What is the specific question or topic? (The tighter the question, the
more useful the synthesis.)
- What kind of sources should be prioritized — recent news, academic
research, industry reports, product documentation, public company data?
- How many sources? Recommend 4–6 for most topics. More than 8 adds noise.
- What is the deliverable — a one-page brief, a comparison table, a
detailed report?
- Is there a time horizon? ("Last 12 months" vs "all time" changes which
sources matter.)
Write the confirmed research brief as a single paragraph before proceeding.
Step 2 — Identify the source types
Choose 4–6 source types appropriate to the question. Common combinations:
- For market research: industry reports, competitor websites, news articles,
analyst commentary, customer reviews
- For decision support: expert opinion pieces, case studies, official
documentation, statistical data
- For competitive intelligence: company websites, job postings, press
releases, product reviews, social commentary
Name each source type explicitly. Workers perform better with a specific
assignment than a vague one.
Step 3 — Dispatch parallel workers
Write one research prompt per source type, then combine them into a single
parallel dispatch instruction:
"Use parallel workers to research [topic]. Assign one worker per source
type below. Each worker should gather the 3–5 most relevant pieces of
information from their assigned source type and save findings to a file
named research-[source-type].md. Workers should not share findings with
each other yet.
Source assignments:
- Worker 1: [source type 1]
- Worker 2: [source type 2]
- Worker 3: [source type 3]
- Worker 4: [source type 4]"
Step 4 — Collect and compare the raw findings
Once all workers have saved their files, read all research files and perform
a cross-source comparison. For each major theme or claim, note:
- Which sources agree
- Which sources contradict each other
- Which sources provide data vs opinion
- What is missing from all sources
Save this comparison to research-comparison.md.
Step 5 — Synthesize into findings with confidence ratings
Write the final synthesis. For each key finding, assign a confidence rating:
- High confidence: Three or more independent sources agree, at least one
is data-backed.
- Medium confidence: Two sources agree, or one strong source with no
contradictions found.
- Low confidence: Only one source, or sources conflict without resolution.
Present each finding as: [Finding statement] — [Confidence: High/Medium/Low]
followed by one sentence explaining why.
Step 6 — Deliver the synthesis report
Structure the final report as:
- Research question (one sentence)
- Key findings (5–8 bullet points with confidence ratings)
- Points of disagreement (where sources conflict and why it matters)
- Gaps (what was not found and where to look next)
- Recommended action (what the user should do with this information)
Save to research-synthesis-[topic]-[date].md and present the key findings
directly in the conversation.
Step 7 — Offer a follow-up drill-down
Ask: "Is there any finding you want to go deeper on? I can dispatch a
focused worker on that specific question."
This turns a broad synthesis into a targeted investigation without starting over.
Compounds With
- parallel-power — the parallel dispatch in Step 3 is the core engine
- connected tools — web search, document access, and database connections
all expand the source range available to workers
- output formatting — the final synthesis can be reformatted into a
slide deck, email brief, or client report
Quality Checks
Before finishing, verify:
Output Format
# Research Synthesis: [Topic]
Research question: [One-sentence statement of what was investigated]
Date: [Date] | Sources queried: [number] | Scope: [time horizon]
---
## Key Findings
1. [Finding statement] — **Confidence: High**
*[One sentence explaining why: which sources agreed, whether data-backed]*
2. [Finding statement] — **Confidence: Medium**
*[One sentence explaining why: sources that agreed, any caveats]*
3. [Finding statement] — **Confidence: Low**
*[One sentence explaining why: single source, conflict, or limited data]*
[Continue for 5–8 total findings]
---
## Points of Disagreement
**[Topic of disagreement]:**
- Source A says: [position]
- Source B says: [position]
- Why it matters: [implication for the user's question]
[Repeat for each material conflict]
---
## Gaps
What was not found and where to look next:
- [Gap 1] — Suggested next source: [where to look]
- [Gap 2] — Suggested next source: [where to look]
---
## Recommended Action
[1–3 sentences. What the user should do, decide, or investigate further based on the synthesis.
Grounded in the high-confidence findings.]
---
*Sources queried: [list source types used]*
*Files saved: research-[source]-[date].md (per worker), research-comparison.md, this file*
Examples
Example 1 — Market research:
User types: "Research synthesizer — is there demand for async video tools in mid-market B2B?"
Result: Cowork dispatches four workers (industry reports, competitor analysis, customer reviews, analyst
commentary), collects findings, compares where sources agree and conflict, and delivers a synthesis with
confidence-rated findings — saving the full report as research-synthesis-async-video-b2b-[date].md.
Example 2 — Competitive intelligence:
User types: "Deep dive into how Notion positions itself vs. Confluence for enterprise teams"
Result: Workers cover company websites, job postings, press releases, product reviews, and social
commentary. The synthesis surfaces where positioning claims align with user perception and where they
diverge — flagging gaps in the competitive story with a confidence rating for each finding.
Example 3 — Decision support:
User types: "What does the evidence say about four-day work weeks and productivity?"
Result: Cowork prioritizes academic research, expert commentary, and case studies from companies that
have tried it. The synthesis separates high-confidence findings (backed by multiple studies) from low-
confidence claims (single source or methodologically weak), giving the user a clear picture of what the
evidence actually supports.
Troubleshooting
Issue: "Confidence ratings all came back Low — nothing feels settled"
This is accurate data, not a failure. It means the topic is genuinely contested or under-researched. The
synthesis is still valuable: it maps the landscape of disagreement and shows where more authoritative
sources are needed. Use the Gaps section and drill-down offer to identify the next research step.
Issue: "Workers found conflicting information and I don't know which to trust"
The Points of Disagreement section exists for exactly this. Look at the source type behind each claim:
data-backed findings from primary research outweigh opinion pieces. If two credible sources conflict,
the finding gets a Low or Medium confidence rating and a note — so you can see the disagreement rather
than have it hidden in a blended average.
Issue: "The synthesis is too broad — I need more depth on one finding"
Use the drill-down offer at Step 7. Say: "Go deeper on finding 3." The skill dispatches a focused worker
on that specific question, running a targeted investigation without restarting the full synthesis.
Related Skills
See also: content-engine — uses research synthesis as the foundation for blog posts and social content.
Related: weekly-business-pulse — applies a similar multi-source aggregation pattern to your own tools.
Related: meeting-machine — for bringing synthesized research into a pre-meeting prep package.