Produces a structured Research Summary document (findings, sources, attributions) from targeted web queries using Brave Search and web_fetch. Use when: 'research this online', 'find current information about X', 'verify this claim', 'gather sources on Y', 'search for what the field says about Z'.
Instrucciones de origen · Vista previa de solo lectura
name
web-research
model
sonnet
description
Produces a structured Research Summary document (findings, sources, attributions) from targeted web queries using Brave Search and web_fetch. Use when: 'research this online', 'find current information about X', 'verify this claim', 'gather sources on Y', 'search for what the field says about Z'.
category
continuous-learning
triggers
["research this online","find current information about","verify this claim","gather sources on","search for what the field says about"]
tier
1
agents
["primary"]
tool_dependencies
["web_tools"]
inputs
[{"name":"query","type":"string","description":"The research question or topic to investigate online","required":true}]
outputs
[{"name":"research_summary","type":"ref","format":"cas-ref","description":"Structured Research Summary document with findings, sources, and attributions from web queries"}]
Web Research Skill
Version: 1.1
Created: 2026-02-02
Author: Cipher (self-taught)
Purpose: Effective web research using Brave Search API and web_fetch for content extraction
Overview
This skill encodes best practices for web research — finding, evaluating, and synthesizing information from online sources. It provides patterns for search query formulation, source evaluation, information synthesis, and attribution. Web research is not about collecting links — it's about building understanding from reliable sources.
Output templates for all research modes are in references/research-output-templates.md.
Core Tools
Available Tools:
web_search(query, count, country, search_lang, ui_lang, freshness) — Brave Search API for finding sources
web_fetch(url, extractMode, maxChars) — Extract readable content from URLs (markdown/text)
Parameters:
query: Search query string (required)
count: Number of results (1-10, default: 5)
country: 2-letter country code for regional results (default: 'US')
search_lang: ISO language code for search results
ui_lang: ISO language code for UI elements
freshness: Time filter for results (pd=past 24h, pw=past week, pm=past month, py=past year)
url: HTTP or HTTPS URL to fetch
extractMode: 'markdown' or 'text' (default: 'markdown')
maxChars: Maximum characters to return (truncates when exceeded)
When to Use This Skill
Investigating a topic that requires current information
Finding sources for research or specifications
Verifying claims or facts
Gathering competitive intelligence or landscape scans
Understanding a technology, framework, or practice
Finding documentation or examples
Research Workflow
Step 1: Define Your Research Question
Before searching, clarify:
What specific question am I trying to answer?
What level of detail do I need? (overview vs. deep dive)
Is this time-sensitive? (recent events, API versions, industry news)
What context do I already have? (avoid re-searching known info)
Capture sources cited — Link back to original content
Step 5: Synthesize Findings
Goal: Answer the research question, not regurgitate content.
Synthesis template — see references/research-output-templates.md for the full Research Synthesis format.
Synthesis principles:
Be specific — Avoid "some say," "likely," "possibly"
Attribute claims — "According to [Source], X is true" not "X is true"
Note contradictions — "Source A claims X, but Source B says Y"
Signal uncertainty — "Could not verify" or "Limited evidence available"
Research Modes
Mode 1: Verification Research
Use when: Verifying a specific claim, fact, or data point
Process:
Formulate specific query: "[claim] verify"
Search 3-5 sources
Cross-reference across sources
Note consensus or conflict
Output: Verification document with Verdict (Confirmed / False / Partially Confirmed / Could Not Verify), Evidence section listing each source's position — see references/research-output-templates.md
Mode 2: Deep Dive Research
Use when: Need comprehensive understanding of a complex topic
Process:
Start with overview query: "[topic] overview"
Identify subtopics from results
Query each subtopic: "[topic] [subtopic] details"
Fetch and read 2-3 sources per subtopic
Synthesize into structured overview
Output: Deep Dive document organized by subtopics with cross-subtopic synthesis — see references/research-output-templates.md
Mode 3: Landscape Scan
Use when: Broad pattern recognition across many topics
Process:
Formulate 5-10 related queries
Execute searches (1-2 sources each)
Extract patterns and themes
Create opportunity or comparison matrix
Output: Landscape Scan document with themes, key players table, and gaps list — see references/research-output-templates.md
Quality Checklist
Before concluding web research, verify:
Source Quality
At least 2-3 sources consulted (unless verification)
Sources are credible (official docs, established news, experts)
Sources are recent (within 1-3 years, unless historical context)
Conflicting information is noted
Content Quality
Specific claims are supported by evidence
Attribution is clear (which source said what)
Uncertainty is signaled (couldn't verify, limited data)
Filler is minimized (no generic advice)
Synthesis Quality
Research question is answered directly
Key findings are specific and actionable
Sources are cited with URLs
Open questions or gaps are noted
Common Pitfalls to Avoid
Single-source confirmation — Finding one source that confirms belief — cross-reference across 2-3 sources
Over-fetching — Reading 50 pages for one query — focus on 2-5 relevant sources
Generic queries — "AI tools" returns 10M results — use specific queries with context
No attribution — "Studies show X" — attribute: "According to [Source], X"
Outdated data — Using 2019 info for a 2026 decision — use freshness filter
research-modes — For structuring deep vs. wide research phases
specification-writer — When research feeds into spec writing
seed-extraction — When research reveals reusable patterns
workspace-navigation — When organizing research findings in shared workspaces
Pattern:
web_search() -> web_fetch() -> Extract insights ->
research-modes(structure) OR specification-writer(draft) OR seed-extraction(capture)
Output
A Research Summary markdown document answering the research question
Saved to the project's docs/research/ or scouts/ directory
Named: [date]_[topic]_web_research.md
Includes: summary, key findings, supporting details, cited sources with URLs, open questions
Examples
Scenario 1: "Find current information about WebSocket performance benchmarks for Go" → Verification/Deep Dive document with 3-5 authoritative sources, specific numbers, attribution per claim, and open questions flagged
Scenario 2: "Search for what the field says about AI agent orchestration patterns" → Landscape Scan document with theme clusters, key tool/framework table, and identified gaps across 8-10 sources
Edge Cases
Paywalled content: Note the source in the synthesis as "paywalled, snippet only" and extract what is available from the search snippet; do not fabricate full content
Contradictory authoritative sources: Surface the contradiction explicitly; do not pick one silently — present both and note the disagreement
Topic with no recent sources (>2 years old): Label findings as potentially outdated; recommend confirming with a domain expert or official changelog
Query returns zero relevant results: Reformulate with 2-3 alternative phrasings before concluding the topic is unresearchable
Anti-Patterns
Fetching the full text of 10+ pages when 2-3 targeted extractions answer the question — token cost with no quality gain
Summarizing sources in the order they were found rather than organizing findings by theme — produces a list, not a synthesis
Accepting a source as authoritative because its domain sounds credible without checking the actual author or date
Using web research for questions that can be answered from the existing codebase or memory — always check local context first
Related Skills:
research-modes — Deep vs. wide research structuring
specification-writer — Research to spec conversion
seed-extraction — Pattern extraction from research findings
Last Updated: 2026-04-08
Maintained By: Cipher
Status: Active
