What is 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.

Use it for technology evaluations, competitive analysis, market research, due diligence, or any topic where a thorough, source-linked report is needed.

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.

deep-research — Skill for Claude Code and Codex by majiang213

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.

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.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/majiang213/openclaw-mas/deep-research/github.svg)](https://agentmods.dev/skills/majiang213/openclaw-mas/deep-research)

Your own site

<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/deep-research"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/deep-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/deep-research"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

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. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00048	$0.01146
Opus 5.5	$0.00019	$0.00458
Sonnet 5.5	$0.00010	$0.00229
Haiku 4.5	$0.00005	$0.00115

Measured 1mo ago against content hash 2d631427fc9a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 1mo ago.

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 — 2 lines 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:

firecrawl — firecrawl_search, firecrawl_scrape, firecrawl_crawl
exa — web_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.

1mo ago 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 6mo ago), licensed MIT. It adds 48 tokens to every session and 1,146 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 94% identical to deep-research, differing in 2 lines, and is treated as a copy.

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