Web Research

Web Research

Overview

Structured deep research that produces verified, organised findings with confidence levels and source evaluation. Any agent can invoke this skill when they need information — it replaces ad-hoc searching with a systematic methodology. Output is saved to research/[topic]/ for reuse.

When to Use

• Agent needs factual data to make a decision
• Challenger needs to verify claims
• Forge needs domain context before design
• research-for-skills needs domain knowledge before writing a skill
• Any task where "I think" should be replaced with "the evidence shows"

Internet Reachability Check

Before running web searches, check if internet is available via the knowledge-grounding manifest:

INTERNET=$(jq -r '.internet_reachable' ~/.claude/state/sources.json 2>/dev/null || echo "unknown")

If internet_reachable is false:

• Do NOT attempt web searches (they will hang or fail)
• Suggest local sources instead: wikis, project docs, configured doc_paths
• Read active sources from ~/.claude/state/sources.json to suggest alternatives

If the manifest does not exist, run bash ~/.claude/skills/knowledge-grounding/scripts/discover.sh discover --silent first.

Antigravity (agy) Cross-Verification

When available, the Antigravity CLI (agy) provides an additional research source from a different model family. Invoke it headless with stdin closed (mandatory — see the antigravity-cli skill):

timeout 600 agy -p "Verify: <claim>. Cite sources." < /dev/null

Use it to:

• Cross-verify findings from WebSearch with a different model/search backend
• Get second-model answers for freshness-sensitive topics (latest versions, recent changes)
• Run parallel verification: WebSearch + agy + Codex (/codex:rescue) for triangulation
• Synthesize large research outputs that exceed Claude's working context (agy handles large-context analysis well)

(See codex-orchestration / cross-cli-deliberation for full delegation patterns.)

The Research Process

1. SCOPE    → Define what we need to know (sub-questions)
2. SEARCH   → Parallel agents search different angles
3. EVALUATE → Apply source evaluation to every finding
4. VERIFY   → Triangulate across 3+ independent sources
5. FLAG     → Mark what was NOT found (gaps)
6. STRUCTURE → Organise with confidence levels
7. SAVE     → Store in research/[topic]/

Step 1: Scope — Decompose the Question

Break the research topic into 4-5 searchable sub-questions using MECE (Mutually Exclusive, Collectively Exhaustive):

Topic: "Is Redis suitable for our session storage?"

Sub-questions:
1. What are Redis's session storage capabilities and limits?
2. What are the alternatives (Memcached, DB, JWT) and trade-offs?
3. What are Redis failure modes and data loss risks?
4. What's the operational cost (hosting, monitoring, maintenance)?
5. What do practitioners report from production use?

Rule: If you can't break it into sub-questions, the topic is too vague. Refine it first.

Research Levels

Choose the level BEFORE starting. The calling agent or user specifies the level. When not specified, use the decision guide below.

SHORT — Quick Verification (seconds to 1 minute)

Use when: Verifying a single claim, checking if a library exists, confirming a version number, getting one specific fact.

Examples: "Does ibm_db support Python 3.14?", "What's the current Flask version?", "Is FAQ schema still generating rich results?"

MEDIUM — Focused Research (2-5 minutes)

Use when: Understanding a specific topic, comparing 2-3 options, getting current best practices for a focused area, verifying multiple related claims.

Examples: "Best deployment pattern for Flask + Gunicorn in 2026", "Redis vs Memcached for session storage", "Current state of Google FAQ schema support"

LONG — Deep Research (5-15 minutes)

Use when: Creating a new skill, understanding an entire domain, multi-faceted topic with many subtopics, need comprehensive coverage with challenger review.

Examples: "Full SEO landscape 2026", "Python parallelism patterns", "WooCommerce security best practices", "Docker admin patterns"

Decision Guide — How to Choose Level

Is this a single fact or version check?
  → SHORT

Is this a focused question with 1-2 sub-questions?
  → MEDIUM

Does it have 3+ sub-questions, or will it become a skill?
  → LONG

Still unsure? Ask:
  "How many sub-questions does this break into?"
    1-2  → MEDIUM
    3+   → LONG
    0    → SHORT (it's just a fact check)

Callers can override: An agent requesting research can specify the level. If not specified, use the decision guide. When in doubt, start MEDIUM — escalate to LONG only if findings are insufficient.

Step 2: Search — Execute at Chosen Level

SHORT: Inline Search

No agents spawned. The requesting agent runs 1-3 WebSearch queries directly and returns the answer with source.

MEDIUM: Focused Agents

Spawn 1-2 research agents, each covering a sub-question:

"Research [SUB-QUESTION]. Find:
- Current best practices (2024-2026)
- Data points with specific numbers and sources
- Official documentation references
- Contradicting viewpoints if they exist

For every claim, note the source URL and date.
Flag anything you searched for but couldn't find.
DO NOT make up data. If uncertain, say so."

LONG: Full Research Team

Spawn 3-5 parallel agents + 1 challenger:

Research agents (parallel):
"Research [SUB-QUESTION] deeply. Find:
- Current best practices with specific data/tools/versions
- What's changed since 2023-era advice
- Anti-patterns — common mistakes and outdated advice
- Benchmarks/data points to include
- Practitioner experience (Reddit, HN, Stack Overflow)
- Actionable rules an AI agent should follow

Use WebSearch extensively. Be specific — no generic advice.
For every claim, note source URL and date.
Flag anything searched for but not found."

Challenger agent (after research completes):
"Review all findings for contradictions, vendor bias, outdated
claims, and gaps. Verify key statistics. Flag questionable data."

Step 3: Evaluate — Source Assessment

Apply the SIFT method (Stop, Investigate, Find better, Trace claims) to every source:

Source Trust Hierarchy

Red Flags in Sources

• No date published (reject for any fast-moving topic)
• Statistics without named study/methodology
• Same stat cited across 10 blogs but no original source (circular citation / citogenesis)
• "Studies show" without naming the study
• Vendor's own case study proving their product works
• Numbers that are too precise for the claim ("exactly 94% accuracy")

Step 4: Verify — Triangulation

Every key finding must be triangulated across 3+ independent sources.

Deliberately search for contradicting evidence: After finding support for a claim, search for "[claim] wrong", "[claim] criticism", "[claim] debunked".

Step 5: Flag — Information Gaps

Explicitly state what you searched for but could NOT find. This is as valuable as what you did find.

### Information Gaps

| Searched For | Result |
|-------------|--------|
| Redis session storage benchmark at 100K concurrent users | NOT FOUND — no public benchmarks at this scale |
| Comparison of Redis vs Valkey for sessions (post-fork) | INSUFFICIENT — only vendor blog posts, no independent comparison |
| GDPR implications of Redis session data in EU | PARTIAL — found general guidance but no Redis-specific legal opinion |

Step 6: Structure — Confidence Levels

Every finding gets a confidence level:

Step 7: Save — Research Output

Save all findings to research/[topic]/:

research/
  [topic]/
    INDEX.md              # Summary of findings + confidence levels
    R1-[subtopic].md      # Detailed findings per sub-question
    R2-[subtopic].md
    sources.md            # Annotated source list

INDEX.md Template

# Research: [Topic]

**Date:** [YYYY-MM-DD]
**Requested by:** [Agent/User]
**Sub-questions:** [List]

## Key Findings

| # | Finding | Confidence | Source |
|---|---------|-----------|--------|
| 1 | [Finding] | VERIFIED | [Source + date] |
| 2 | [Finding] | LIKELY | [Source + date] |
| 3 | [Finding] | CONTRADICTORY | [Source A] vs [Source B] |

## Information Gaps

| Searched For | Result |
|-------------|--------|
| [Query] | NOT FOUND / INSUFFICIENT |

## Contradictions Found

| Claim | Source A Says | Source B Says |
|-------|-------------|---------------|
| [Topic] | [Position + source] | [Counter-position + source] |

## Detailed Findings

See individual research files (R1, R2, etc.) for full evidence.

Integration with Other Skills

Search Technique Quick Reference

Google Advanced Operators

Platform-Specific Searches

Anti-Patterns