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skills/nimble-web-expert/references/nimble-search/search-focus-modes.md
6.47 KB · Oct 3, 2026 · 06:11 UTC
--- name: nimble-search-focus-modes-reference description: | Decision tree for selecting the right --focus mode for nimble search. Load when unsure which focus to use. Contains: mode-by-mode guide, example queries per mode, combination strategies, subagent scaling. --- # Focus Modes Reference Detailed guide for selecting the right `--focus` for your search query. ## Decision Tree ``` What are you searching for? | |-- A person? ................... --focus social (+ parallel general) |-- A company/organization? ..... --focus general (+ parallel news) |-- Code, docs, or technical? ... --focus coding |-- Current events or news? ..... --focus news (+ parallel social for reactions) |-- Research papers? ............ --focus academic |-- Products or prices? ......... --focus shopping |-- A local business or place? .. --focus location |-- Geographic/regional data? ... --focus geo |-- General/unsure? ............. --focus general ``` ## Focus Selection by Intent | Query Intent | Primary Focus | Secondary (parallel) | Why | | ------------------------- | ------------- | -------------------- | ---------------------------------------------------------------------------------------------------- | | Research a **person** | `social` | `general` | Social searches LinkedIn/X/YouTube directly via subagents; general covers blogs, news, company pages | | Research a **company** | `general` | `news` | General for overview; news for recent developments | | Find **code/docs** | `coding` | — | Targets Stack Overflow, GitHub, docs sites | | Current **events** | `news` | `social` | News for articles; social for reactions/commentary | | Find a **product/price** | `shopping` | — | Searches e-commerce sites | | Find a **place/business** | `location` | `geo` | Local business lookup | | Find **research papers** | `academic` | — | Targets scholarly sources | | **General/unsure** | `general` | — | Broad web search (default) | **Always run parallel searches with multiple focus when depth matters.** ## Mode Details ### general (default) Standard web search across all sources. Use when no specific mode applies or for broad queries. - Best for: overviews, general questions, company pages, blogs - Speed: fastest (1-2s with `--search-depth lite`) ### coding Targets programming resources: Stack Overflow, GitHub, official docs, MDN, dev blogs. - Best for: API references, code examples, debugging, framework docs - Tip: include the language/framework name in the query for better targeting ### news Current events and recent articles from news outlets and media sites. - Best for: breaking news, recent developments, industry updates - Tip: combine with `--time-range` to control recency (hour, day, week, month) ### academic Scholarly content: research papers, journals, university publications. - Best for: scientific research, citations, peer-reviewed studies - Tip: use specific terminology and author names for better precision ### shopping E-commerce sites and product listings. Uses subagents for Amazon, Target, etc. - Best for: product comparisons, pricing, reviews, availability - Note: uses `--max-subagents` (default 3) for parallel e-commerce searches ### social Social media platforms: LinkedIn, X/Twitter, YouTube, Reddit, forums. Uses subagents. - Best for: people research, public profiles, community discussions, opinions - Note: returns LinkedIn/X/YouTube data directly via subagents — no need to extract those URLs - Note: uses `--max-subagents` (default 3) for parallel social platform searches ### geo Geographic and regional information. - Best for: climate data, regional statistics, geographic features, area-specific info - Tip: combine with `--country` for localized results ### location Local business and place-specific queries. - Best for: restaurants, shops, services in a specific area - Tip: include the city/area name in the query ## Combination Strategies For in-depth research, run 2-3 focus modes in parallel to maximize coverage: | Research Goal | Parallel Combination | Query Strategy | | -------------------- | ----------------------------- | --------------------------------------------------------------- | | Person profile | `social` + `general` | Name + job title + company | | Company deep dive | `general` + `news` + `social` | Company name, then news for recent events, social for sentiment | | Technical evaluation | `coding` + `general` | Technology name + use case | | Market research | `shopping` + `news` | Product category + "market" or "trends" | | Local research | `location` + `general` | Business type + city name | ## Mode Comparison | Mode | Speed | Subagents | Best Sources | Use Case | | ---------- | ------ | --------- | ----------------- | ------------------ | | `general` | Fast | No | All web | Default, overviews | | `coding` | Fast | No | GitHub, SO, docs | Programming | | `news` | Fast | No | News outlets | Current events | | `academic` | Fast | No | Journals, papers | Research | | `shopping` | Medium | Yes (3) | E-commerce | Products, prices | | `social` | Medium | Yes (3) | LinkedIn, X, YT | People, opinions | | `geo` | Medium | Yes (3) | Maps, regional | Geographic data | | `location` | Medium | Yes (3) | Local directories | Local business | Modes that use subagents (`shopping`, `social`, `geo`, `location`) are slightly slower but return richer, platform-specific data. Control parallelism with `--max-subagents` (1-10, default 3).
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