Deep research

Skill sarbak/strategy-skills/deep-research

Strategy, SEO/GEO, and analytics skills for Claude Code — by Emotion Machine (emotionmachine.com)

Install

npx -y skills add sarbak/strategy-skills --skill deep-research

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Run deep research on specific questions to validate assumptions, check facts, and discover recent developments. Pairs with opportunity-analysis and storyline-synthesis for full strategy workflows. Use when the user wants to research specific questions, validate business assumptions, fact-check claims, or investigate a market. Also trigger when someone says "research this", "is this actually true?", "validate these assumptions", or "what's the current state of [topic]?"

SKILL.md

4.9 KB, as published. Nobody here has run it

Deep Research

Run focused research on specific questions to validate assumptions, check facts, and discover what's changed recently.

This process has 8 steps. Complete every step in order. Do not skip steps. When reporting progress, label each step as shown (e.g., "Step 3/8").

Step 1/8 -- Determine research questions

If the user provides specific questions as arguments, use those.
If no questions provided, look for a DEEP_RESEARCH_REQUEST.md or strategy/DEEP_RESEARCH_REQUEST.md in the working directory.
If neither exists, ask the user what they want researched.

Step 2/8 -- Check for overlap with existing work

Before researching anything, scan all existing docs in the project's strategy/analysis subfolder. Don't re-research what's already answered. Note which questions are already covered (partially or fully) and skip them.

Step 3/8 -- Verify the question hierarchy

Questions must be ordered by how fundamental they are. If a higher-level assumption is wrong, lower-level questions are irrelevant.

Level 0: Does the core capability actually work / is it differentiated?
  +-- Level 1: Is the market structure what we think it is?
       +-- Level 2: Will someone actually pay for this?
            +-- Level 3: Are our specific market picks right?
                 +-- Level 4: Can we execute? (timing, legal, competitive dynamics)

Research top-down. Don't research Level 3 until Level 0-1 are validated. Assign each question a level.

Step 4/8 -- Research Level 0-1 questions

For each question at Level 0-1:

Step 4a/8 -- Form a specific query

Write a well-formed, specific query with context. Tips:

BAD: "Is the market big?"
GOOD: "How many SaaS companies in the US currently pay for third-party pricing benchmarking data, who are the top 3 providers, and what do they charge?"
Include context in the query: "In the context of [industry] companies evaluating [specific service]..."
Ask for specific numbers, company names, and recent developments
One focused question per query -- don't combine multiple topics

Step 4b/8 -- Execute the search

Use available research tools (Perplexity MCP, WebSearch, WebFetch, or other configured search tools) to find answers.

Step 4c/8 -- Record findings

For each question, record:

What we assumed vs. what's actually true (with sources)
Red flags -- assumptions that are significantly wrong
New opportunities the research reveals

Step 5/8 -- Assess whether to proceed

After Level 0-1 answers come back:

If confirmed -> proceed to Level 2-3 questions in Step 6/8
If partially wrong -> reframe the thesis, rewrite lower-level questions before proceeding
If fundamentally wrong -> stop. Report findings. The thesis needs restructuring.

Step 6/8 -- Research Level 2-4 questions

Repeat the same sub-steps as Step 4/8 (form query -> execute -> record) for each remaining question at Levels 2-4. After each level, reassess whether the lower-level questions are still relevant.

Step 7/8 -- Write the results document

Save results to strategy/DEEP_RESEARCH_RESULTS.md (or alongside the request file). Structure per question:

### Question: [the specific question]

**Our assumption:** [what we believed]

**What's actually true:** [findings with sources]

**What's changed recently:** [any developments since our analysis]

**Red flags:** [anything that invalidates our thesis]

**New opportunities:** [anything we didn't see before]

Step 8/8 -- Summary and share

Write a summary section at the end with:

(a) Assumptions confirmed
(b) Assumptions wrong
(c) Storyline changes needed
(d) New questions raised by the research

Rules

Research ONLY the critical questions. Don't expand scope.
Cite sources for every factual claim.
Be honest when you can't find a definitive answer -- "unclear, needs expert interview" is a valid result.
After all questions are researched, the summary must clearly state which assumptions survived and which didn't.

Tips for writing good research queries

BAD: "Is the market big?"
GOOD: "What is the total addressable market for [specific product category] in [geography] as of 2025, and which companies currently serve this market?"
Include context: "In the context of [industry] companies evaluating [specific capability]..."
Ask for specific numbers, company names, and recent developments
One focused question per query -- don't combine multiple topics