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Get Started Free →Systematic multi-angle web research methodology.
.claude/skills/hezaohezao-deep-research/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✓→✗ | ▼ Worse | -43% | 0% |
| case-18 | ✓→✗ | ▼ Worse | -35% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 326% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 206% | 0% |
| case-06 | ✓→✓ | = Same ✓ | 164% | 0% |
Systematic methodology for thorough web research. Load this skill BEFORE starting any content generation task to ensure information from multiple angles, depths, and sources.
Always load when:
real-world information
Never generate content based solely on general knowledge. A single search query is NEVER enough.
Start with broad searches to understand the landscape:
themes, angles needing deeper exploration
For each important dimension identified, conduct targeted research:
browse_page to read important sources in full,not just snippets
Ensure comprehensive coverage by seeking diverse information types:
| Information Type | Purpose | Example Searches | |-----------------|---------|------------------| | Facts & Data | Concrete evidence | "statistics", "data", "market size" | | Examples & Cases | Real-world applications | "case study", "example", "implementation" | | Expert Opinions | Authority perspectives | "expert analysis", "interview", "commentary" | | Trends & Predictions | Future direction | "trends 2026", "forecast", "future of" | | Comparisons | Context and alternatives | "vs", "comparison", "alternatives" | | Challenges & Criticisms | Balanced view | "challenges", "limitations", "criticism" |
Before proceeding to content generation, verify:
If any answer is NO, continue researching before generating content.
# Be specific with context
"enterprise AI adoption trends 2026"
# Include authoritative source hints
"[topic] research paper"
"[topic] McKinsey report"
# Search for specific content types
"[topic] case study"
"[topic] statistics"
# Use temporal qualifiers — use the ACTUAL current year
"[topic] 2026"
"[topic] latest"Always check the current date before forming search queries:
| User intent | Temporal precision | Example query | |---|---|---| | "today / just released" | Month + Day | "tech news February 28 2026" | | "this week" | Week range | "technology releases week of Feb 24 2026" | | "recently / latest" | Month | "AI breakthroughs February 2026" | | "this year / trends" | Year | "software trends 2026" |
Use browse_page to read full content when:
Research is iterative:
Research is sufficient when you can confidently answer:
After completing research, you should have:
Only then proceed to content generation.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 63,029 | 10,906 | -83% | 1 | 1 | 0% | 8,479 | 1,691 | -80% | 0 | 0 | — |
case-02 | fail→fail | 58,975 | 14,152 | -76% | 1 | 1 | 0% | 5,763 | 2,082 | -64% | 0 | 0 | — |
case-03 | fail→fail | 42,497 | 10,667 | -75% | 1 | 1 | 0% | 5,968 | 1,737 | -71% | 0 | 0 | — |
case-04 | pass→pass | 2,977 | 4,318 | +45% | 1 | 1 | 0% | 411 | 1,750 | +326% | 0 | 0 | — |
case-05 | pass→pass | 3,686 | 2,960 | -20% | 1 | 1 | 0% | 550 | 1,681 | +206% | 0 | 0 | — |
case-06 | pass→pass | 6,513 | 8,859 | +36% | 1 | 1 | 0% | 1,021 | 2,693 | +164% | 0 | 0 | — |
case-07 | pass→pass | 10,717 | 12,350 | +15% | 1 | 1 | 0% | 1,591 | 3,014 | +89% | 0 | 0 | — |
case-08 | fail→fail | 13,888 | 10,430 | -25% | 1 | 1 | 0% | 2,065 | 1,734 | -16% | 0 | 0 | — |
case-09 | pass→fail | 18,046 | 10,036 | -44% | 1 | 1 | 0% | 2,715 | 1,550 | -43% | 0 | 0 | — |
case-10 | pass→pass | 15,339 | 13,357 | -13% | 1 | 1 | 0% | 2,391 | 3,264 | +37% | 0 | 0 | — |
case-11 | pass→pass | 14,339 | 11,465 | -20% | 1 | 1 | 0% | 2,065 | 2,672 | +29% | 0 | 0 | — |
case-12 | fail→fail | 9,962 | 6,626 | -33% | 1 | 1 | 0% | 1,265 | 2,049 | +62% | 0 | 0 | — |
case-13 | fail→fail | 17,095 | 31,150 | +82% | 1 | 1 | 0% | 2,492 | 1,527 | -39% | 0 | 0 | — |
case-14 | pass→pass | 14,562 | 17,304 | +19% | 1 | 1 | 0% | 2,053 | 3,897 | +90% | 0 | 0 | — |
case-15 | pass→pass | 7,328 | 7,846 | +7% | 1 | 1 | 0% | 1,148 | 2,259 | +97% | 0 | 0 | — |
case-16 | pass→pass | 13,414 | 11,833 | -12% | 1 | 1 | 0% | 1,980 | 2,705 | +37% | 0 | 0 | — |
case-17 | pass→pass | 11,904 | 14,453 | +21% | 1 | 1 | 0% | 1,728 | 2,722 | +58% | 0 | 0 | — |
case-18 | pass→fail | 61,374 | 25,939 | -58% | 1 | 1 | 0% | 2,845 | 1,862 | -35% | 0 | 0 | — |
case-19 | fail→fail | 8,292 | 8,387 | +1% | 1 | 1 | 0% | 1,202 | 2,366 | +97% | 0 | 0 | — |
case-20 | pass→pass | 16,064 | 13,150 | -18% | 1 | 1 | 0% | 2,140 | 3,139 | +47% | 0 | 0 | — |
case-21 | fail→fail | 6,740 | 9,593 | +42% | 1 | 1 | 0% | 967 | 2,493 | +158% | 0 | 0 | — |
case-22 | fail→fail | 10,700 | 17,628 | +65% | 1 | 1 | 0% | 1,401 | 2,417 | +73% | 0 | 0 | — |
case-23 | pass→pass | 33,145 | 18,821 | -43% | 1 | 1 | 0% | 2,403 | 3,628 | +51% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 16 counted toward the lift figure. The other 7 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -9 percentage points is the difference between those two pass rates over the 16 comparable cases. 4 cases got worse with the skill loaded, and they are included in that figure.
Other measured skills in the registry, with their headline benchmark lift.