deep-research

A research workflow for searching multiple web sources, combining the findings, and producing a report with citations. It is intended for questions that need evidence from several sources rather than a quick answer.

In plain words
What is it for?
Use it for technology evaluations, competitive analysis, market research, due diligence, or any topic where a thorough, source-linked report is needed.
Why use it?
It reduces the manual work of searching, checking, and assembling information from different websites. It requires at least one supported web-search service, such as Firecrawl or Exa.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/majiang213/openclaw-mas/deep-research
Any agent
npx skills add majiang213/OpenClaw-MAS --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/majiang213/OpenClaw-MAS

Made for: Claude Code, Codex.

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,146 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00048 $0.01146
Opus 5 $0.00024 $0.00573
Sonnet 5 $0.00010 $0.00229
Haiku 4.5 $0.00005 $0.00115

Measured yesterday against content hash 2d631427fc9a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

deep-research scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

Both together give the best coverage. Configure in `~/.claude.json` or `~/.codex/config.toml`.
Origin

This is a copy

94% identical to deep-research — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

ecc-skills/deep-research/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research

Produce thorough, cited research reports from multiple web sources using firecrawl and exa MCP tools.

When to Activate

  • User asks to research any topic in depth
  • Competitive analysis, technology evaluation, or market sizing
  • Due diligence on companies, investors, or technologies
  • Any question requiring synthesis from multiple sources
  • User says "research", "deep dive", "investigate", or "what's the current state of"

MCP Requirements

At least one of:

  • firecrawlfirecrawl_search, firecrawl_scrape, firecrawl_crawl
  • exaweb_search_exa, web_search_advanced_exa, crawling_exa

Both together give the best coverage. Configure in ~/.claude.json or ~/.codex/config.toml.

Workflow

Step 1: Understand the Goal

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

Break the topic into 3-5 research sub-questions. 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, search using available MCP tools:

With firecrawl:

firecrawl_search(query: "<sub-question keywords>", limit: 8)

With exa:

web_search_exa(query: "<sub-question keywords>", numResults: 8)
web_search_advanced_exa(query: "<keywords>", numResults: 5, startPublishedDate: "2025-01-01")

Search strategy:

  • Use 2-3 different keyword variations per sub-question
  • Mix general and news-focused queries
  • 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:

Read the full file on GitHub · 156 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 156 lines · 48 tokens per session scan B 2d631427fc9a

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 4mo ago), licensed MIT. It adds 48 tokens to every session and 1,146 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 94% identical to deep-research, differing in 1 line, and is treated as a copy.

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