web-search▌
brave/brave-search-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Web search with ranked results, snippets, and support for freshness filters, SafeSearch, and custom ranking via Goggles.
- ›Returns structured results across multiple types: web pages, news, videos, discussions, FAQ, infobox, and locations in a single response
- ›Supports freshness filtering (past day/week/month/year or custom date ranges), SafeSearch levels, and location-aware results via headers
- ›Goggles enable custom result ranking: boost trusted sources, suppress spam, or build focused
Web Search
Requires API Key: Get one at https://api.search.brave.com
Plan: Included in the Search plan. See https://api-dashboard.search.brave.com/app/subscriptions/subscribe
Quick Start (cURL)
Basic Search
curl -s "https://api.search.brave.com/res/v1/web/search?q=python+web+frameworks" \
-H "Accept: application/json" \
-H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}"
With Parameters
curl -s "https://api.search.brave.com/res/v1/web/search" \
-H "Accept: application/json" \
-H "X-Subscription-Token: ${BRAVE_SEARCH_API_KEY}" \
-G \
--data-urlencode "q=rust programming tutorials" \
--data-urlencode "country=US" \
--data-urlencode "search_lang=en" \
--data-urlencode "count=10" \
--data-urlencode "safesearch=moderate" \
--data-urlencode "freshness=pm"
Endpoint
GET https://api.search.brave.com/res/v1/web/search
POST https://api.search.brave.com/res/v1/web/search
Note: Both GET and POST methods are supported. POST is useful for long queries or complex Goggles.
Authentication: X-Subscription-Token: <API_KEY> header
Optional Headers:
Accept-Encoding: gzip— Enable gzip compression
When to Use Web Search
| Feature | Web Search (this) | LLM Context (llm-context) |
Answers (answers) |
|---|---|---|---|
| Output | Structured results (links, snippets, metadata) | Pre-extracted page content for LLMs | End-to-end AI answers with citations |
| Result types | Web, news, videos, discussions, FAQ, infobox, locations, rich | Extracted text chunks, tables, code | Synthesized answer + source list |
| Unique features | Goggles, structured data (schemas), rich callbacks |
Token budget control, threshold modes | Multi-iteration search, streaming, OpenAI SDK compatible |
| Speed | Fast (~0.5-1s) | Fast (<1s) | Slower (~30-180s) |
| Best for | Search UIs, data extraction, custom ranking | RAG pipelines, AI agents, grounding | Chat interfaces, thorough research |
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
q |
string | Yes | - | Search query (1-400 chars, max 50 words) |
country |
string | No | US |
Search country (2-letter country code or ALL) |
search_lang |
string | No | en |
Language preference (2+ char language code) |
ui_lang |
string | No | en-US |
UI language (e.g., "en-US") |
count |
int | No | 20 |
Max results per page (1-20) |
offset |
int | No | 0 |
Page offset for pagination (0-9) |
safesearch |
string | No | moderate |
Adult content filter (off/moderate/strict) |
freshness |
string | No | - | Time filter (pd/pw/pm/py or date range) |
text_decorations |
bool | No | true |
Include highlight markers |
spellcheck |
bool | No | true |
Auto-correct query |
result_filter |
string | No | - | Filter result types (comma-separated) |
goggles |
string | No | - | Custom ranking filter (URL or inline) |
extra_snippets |
bool | No | - | Get up to 5 extra snippets per result |
operators |
bool | No | true |
Apply search operators |
units |
string | No | - | Measurement units (metric/imperial) |
enable_rich_callback |
bool | No | false |
Enable rich 3rd party data callback |
include_fetch_metadata |
bool | No | false |
Include fetched_content_timestamp on results |
Freshness Values
| Value | Description |
|---|---|
pd |
Past day (24 hours) |
pw |
Past week (7 days) |
pm |
Past month (31 days) |
py |
Past year (365 days) |
YYYY-MM-DDtoYYYY-MM-DD |
Custom date range |
Result Filter Values
Filter types: discussions, faq, infobox, news, query, videos, web, locations
# Only web and video results
curl "...&result_filter=web,videos"
Location Headers (Optional)
For location-aware results, add these headers. Lat/Long is sufficient when coordinates are known — the other headers are only needed as a fallback when coordinates are unavailable.
| Header | Type | Description |
|---|---|---|
X-Loc-Lat |
float | User latitude (-90.0 to 90.0) |
X-Loc-Long |
float | User longitude (-180.0 to 180.0) |
X-Loc-Timezone |
string | IANA timezone (e.g., "America/San_Francisco") |
X-Loc-City |
string | City name |
X-Loc-State |
string | State/region code (ISO 3166-2) |
X-Loc-State-Name |
string | State/region full name (e.g., "California") |
X-Loc-Country |
string | 2-letter country code |
X-Loc-Postal-Code |
string | Postal code (e.g., "94105") |
Priority:
X-Loc-Lat+X-Loc-Longtake precedence. When provided, downstream services resolve the location directly from coordinates and the text-based headers (City, State, Country, Postal-Code) are not used for location resolution. Provide text-based headers only when you don't have coordinates. Sending both won't break anything — lat/long simply wins.
Response Format
Response Fields
| Field | Type | Description |
|---|---|---|
type |
string | Always "search" |
query.original |
string | The original search query |
query.altered |
string? | Spellcheck-corrected query (if changed) |
query.cleaned |
string? | Cleaned/normalized query |
query.spellcheck_off |
bool? | Whether spellcheck was disabled |
query.more_results_available |
bool | Whether more pages exist |
query.show_strict_warning |
bool? | True if strict safesearch blocked adult results |
query.search_operators |
object? | Applied search operators (applied, cleaned_query, sites) |
web.type |
string | Always "search" |
web.results[].title |
string | Page title |
web.results[].url |
string | Page URL |
web.results[].description |
string? | Snippet/description text |
web.results[].age |
string? | Human-readable age (e.g., "2 days ago") |
web.results[].language |
string? | Content language code |
web.results[].meta_url |
object | URL components (scheme, netloc, hostname, path) |
web.results[].thumbnail |
object? | Thumbnail (src, original) |
web.results[].thumbnail.original |
string? | Original full-size image URL |
web.results[].thumbnail.logo |
bool? | Whether the thumbnail is a logo |
web.results[].profile |
object? | Publisher identity (name, url, long_name, img) |
web.results[].page_age |
string? | ISO datetime of publication (e.g., "2025-04-12T14:22:41") |
web.results[].extra_snippets |
list[str]? | Up to 5 additional excerpts |
web.results[].deep_results |
object? | Additional links (buttons, links) from the page |
web.results[].schemas |
list? | Raw schema.org structured data |
web.results[].product |
object? | Product info and reviews |
web.results[].recipe |
object? | Recipe details (ingredients, time, ratings) |
web.results[].article |
object? | Article metadata (author, publisher, date) |
web.results[].book |
object? | Book info (author, ISBN, rating) |
web.results[].software |
object? | Software product info |
web.results[].rating |
object? | Aggregate ratings |
web.results[].faq |
object? | FAQ found on the page |
web.results[].movie |
object? | Movie info (directors, actors, genre) |
web.results[].video |
object? | Video metadata (duration, views, creator) |
web.results[].location |
object? | Location/restaurant details |
web.results[].qa |
object? | Question/answer info |
web.results[].creative_work |
object? | Creative work data |
web.results[].music_recording |
object? | Music/song data |
web.results[].organization |
object? | Organization info |
web.results[].review |
object? | Review data |
web.results[].content_type |
string? | Content type classification |
web.results[].fetched_content_timestamp |
int? | Fetch timestamp (with include_fetch_metadata=true) |
web.mutated_by_goggles |
bool | Whether results were re-ranked by Goggles |
web.family_friendly |
bool | Whether results are family-friendly |
mixed |
object? | Preferred display order (see Mixed Response below) |
discussions.results[] |
array? | Forum discussion clusters |
discussions.results[].data.forum_name |
string? | Forum/community name |
discussions.results[].data.num_answers |
int? | Number of answers/replies |
discussions.results[].data.question |
string? | Discussion question |
discussions.results[].data.top_comment |
string? | Top-voted comment excerpt |
faq.results[] |
array? | FAQ entries |
news.results[] |
array? | News articles |
videos.results[] |
array? | Video results |
infobox.results[] |
array? | Knowledge graph entries |
locations.results[] |
array? | Local POI results |
rich.hint.vertical |
string? | Rich result type |
rich.hint.callback_key |
string? | Callback key for rich data |
JSON Example
{
"type": "search",
"query": {
"original": "python frameworks",
"altered": "python web frameworks",
"spellcheck_off": false,
"more_results_available": true
},
"web": {
"type": "search",
"results": [
{
"title": "Top Python Web Frameworks",
"url": "https://example.com/python-frameworks",
"description": "A comprehensive guide to Python web frameworks...",
"age": "2 days ago",
"language": "en",
"meta_url": {
"scheme": "https",
"netloc": "example.com",
"hostname": "example.com",
"path": "/python-frameworks"
},
"thumbnail": {
"src": "https://...",
"original": "https://original-image-url.com/img.jpg"
},
"extra_snippets": ["Additional excerpt 1...", "Additional excerpt 2..."]
}
],
"family_friendly": true
},
"mixed": {
"type": "mixed",
"main": [
{"type": "web", "index": 0, "all": false},
{"type": "web", "index": 1, "all": false},
{"type"How to use web-search on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add web-search
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches web-search from GitHub repository brave/brave-search-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate web-search. Access the skill through slash commands (e.g., /web-search) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★64 reviews- ★★★★★Zara Jain· Dec 28, 2024
Registry listing for web-search matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kaira Harris· Dec 16, 2024
Solid pick for teams standardizing on skills: web-search is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Dec 12, 2024
Solid pick for teams standardizing on skills: web-search is focused, and the summary matches what you get after install.
- ★★★★★Mei Wang· Dec 12, 2024
We added web-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Advait Nasser· Dec 8, 2024
web-search reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Mei Li· Dec 4, 2024
web-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Luis Smith· Dec 4, 2024
Keeps context tight: web-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chen Abebe· Nov 27, 2024
I recommend web-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Arjun Khan· Nov 23, 2024
web-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Chinedu Gonzalez· Nov 19, 2024
Useful defaults in web-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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