lxyeternal/malskillbench/deep-research-pro

Claude Code and agent skill by lxyeternal/malskillbench

Trust tier 2
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Checking that the SKILL.md file is still in the repository.

Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.

Install

npx vskill@latest install lxyeternal/malskillbench/deep-research-pro

SKILL.md

Deep Research Pro 🔬

A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. No paid APIs required — uses DuckDuckGo search.

How It Works

When the user asks for research on any topic, follow this workflow:

Step 1: Understand the Goal (30 seconds)

Ask 1-2 quick clarifying questions:

  • "What's your goal — learning, making a decision, or writing something?"
  • "Any specific angle or depth you want?"

If the user says "just research it" — skip ahead with reasonable defaults.

Step 2: Plan the Research (think before searching)

Break the topic into 3-5 research sub-questions. For example:

  • Topic: "Impact of AI on healthcare"
  • What are the main AI applications in healthcare today?
  • What clinical outcomes have been measured?
  • What are the regulatory challenges?
  • What companies are leading this space?
  • What's the market size and growth trajectory?
Step 3: Execute Multi-Source Search

For EACH sub-question, run the DDG search script:

bash
# Web search
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg "<sub-question keywords>" --max 8
# News search (for current events)
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg news "<topic>" --max 5

Search strategy:

  • Use 2-3 different keyword variations per sub-question
  • Mix web + news searches
  • Aim for 15-30 unique sources total
  • Prioritize: academic, official, reputable news > blogs > forums
Step 4: Deep-Read Key Sources

For the most promising URLs, fetch full content:

bash
curl -sL "<url>" | python3 -c "
import sys, re
html = sys.stdin.read()
# Strip tags, get text
text = re.sub('<[^>]+>', ' ', html)
text = re.sub(r'\s+', ' ', text).strip()
print(text[:5000])
"

Read 3-5 key sources in full for depth. Don't just rely on search snippets.

Step 5: Synthesize & Write Report

Structure the report as:

markdown
# [Topic]: Deep Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*
## Executive Summary
[3-5 sentence overview of key findings]
## 1. [First Major Theme]
[Findings with inline citations]
-Key point ([Source Name](url))
-Supporting data ([Source Name](url))
## 2. [Second Major Theme]
...
## 3. [Third Major Theme]
...
## Key Takeaways
-[Actionable insight 1]
-[Actionable insight 2]
-[Actionable insight 3]
## Sources
1.[Title](url) — [one-line summary]
2....
## Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]
Step 6: Save & Deliver

Save the full report:

bash
mkdir -p ~/clawd/research/[slug]
# Write report to ~/clawd/research/[slug]/report.md

Then deliver:

  • Short topics: Post the full report in chat
  • Long reports: Post the executive summary + key takeaways, offer full report as file

Quality Rules

  1. Every claim needs a source. No unsourced assertions.
  2. Cross-reference. If only one source says it, flag it as unverified.
  3. Recency matters. Prefer sources from the last 12 months.
  4. Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
  5. No hallucination. If you don't know, say "insufficient data found."

Examples

"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"

For Sub-Agent Usage

When spawning as a sub-agent, include the full research request and context:

sessions_spawn(
task: "Run deep research on [TOPIC]. Follow the deep-research-pro SKILL.md workflow.
Read /home/clawdbot/clawd/skills/deep-research-pro/SKILL.md first.
Goal: [user's goal]
Specific angles: [any specifics]
Save report to ~/clawd/research/[slug]/report.md
When done, wake the main session with key findings.",
label: "research-[slug]",
model: "opus"
)

Requirements

  • DDG search script: /home/clawdbot/clawd/skills/ddg-search/scripts/ddg
  • curl (for fetching full pages)
  • No API keys needed!

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
39
Repository forks
8
7-day trend score
18

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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