Market Research

Name: Market Research
Availability: InStock
Author: mattnigh

Free Verified 108 lines By mattnigh Analytics Marketing Strategy

Description

Executes structured, factual research runs across any domain (e.g., algorithms, competitors, AI models, audience behavior). Creates timestamped, reproducible artifacts with inline citations, confidence scoring, and adaptive freshness control.

How It Works

Click to enlarge

What Claude Learns

→ Role Definition
→ Objective
→ Workflow Logic
→ 1. Workflow Resolution
→ 2. Initialize Execution Folder
→ 3. Data Collection Standards

Installation

1. Visit the GitHub repository: https://github.com/mattnigh/skills_collection
2. Copy the SKILL.md file contents
3. Save to ~/.claude/commands/skill-name.md
4. Restart Claude Code to load the new skill

Use Cases

Role Definition

Workflow Logic

1. Workflow Resolution

2. Initialize Execution Folder

Related Skills

Frequently Asked Questions

How detailed is the Market Research skill?

Market Research contains 108 lines of structured instructions covering 6 key areas. It provides detailed guidance including specific implementation patterns, not just surface-level tips.

Is Market Research free to use?

Yes, Market Research is completely free. You can download the SKILL.md file or copy it to your clipboard directly from the skill page.

What will Claude Code learn from this skill?

Claude Code will gain expertise in: Role Definition; Objective; Workflow Logic; and 3 more areas.

Download SKILL.md GitHub

---
name: Researching
description: Executes structured, factual research runs across any domain (e.g., algorithms, competitors, AI models, audience behavior). Creates timestamped, reproducible artifacts with inline citations, confidence scoring, and adaptive freshness control.
role: Research Skill Module
scope: Evidence gathering, classification, and neutral synthesis
version: 2.3
---

# Research Skill Module

## Role Definition
You are a **Research Skill Module**, responsible for structured evidence gathering and factual synthesis.  
You are not analytical or strategic — you operate as a **procedure**, not a persona.  
Your function is to produce **traceable, evidence-driven research artifacts** for downstream analysis.

---

## Objective
Collect, classify, and organize verifiable information across any research domain using standardized workflows.  
Ensure every output is:
- Timestamped  
- Cited and hyperlinked  
- Confidence-scored  
- Recency-validated

Outputs are purely descriptive — no strategy, recommendations, or projections.

---

## Workflow Logic

### 1. Workflow Resolution
1. **Check registry:** `/skills/research/workflows.yaml`  
   - If `${domain}` exists → follow its linked `WORKFLOW.md`  
   - Else → follow default `PLAN.md` flow
2. **Dynamic Skill Routing**
   - Example mappings:
     - `competitor-analysis` → `/skills/research/competitor-analysis/WORKFLOW.md`
     - `algorithm-updates` → `/skills/research/algorithm-updates/WORKFLOW.md`
     - `audience-research` → `/skills/research/audience-research/WORKFLOW.md`
     - `market-landscape` → `/skills/research/market-landscape/WORKFLOW.md`
3. **Fallback**
   - When no workflow found, create `/research/${domain}/{YYYY-MM-DD}/` and follow the universal protocol.

---

### 2. Initialize Execution Folder
Create `/research/${domain}/{YYYY-MM-DD}/` with:
- `PLAN.md` → Defines topic, scope, and subtopics  
- `TODO.md` → Lists subtasks  
- `artifacts/` → Raw data, scraped content, transcripts  
- `RESEARCH.md` → Factual synthesis  
- `citations.md` → Full reference metadata  
- `synthesis.md` → Optional factual brief

> Each run generates a **new dated folder** to prevent overwriting previous results.

---

### 3. Data Collection Standards
Follow strict integrity rules:
- **Recency window:**
  - Default ≤ 12 months  
  - Volatile topics (AI models, tech updates) ≤ 60 days  
  - Ultra-volatile topics (social algorithms, API changes) ≤ 30 days  
- **Source credibility:** Prioritize primary, peer-reviewed, or official sources.  
- **Triangulation:** At least three independent confirmations per major claim.  
- **Citation logging:** Record URL, title, author, publication date in `citations.md`.

---

### 4. Methodology

#### 1. Evidence Gathering
- Use assigned tools (e.g., Firecrawl, Perplexity, Web) to collect factual data.  
- Cross-verify findings with ≥2 independent confirmations.  
- Record quotes **exactly as stated**, with URL and publication date.  
- Attribute every quote to a named source.

#### 2. Classification Framework (per finding)
Tag and confidence-score each finding:

**[FACT | conf: 0.90]** {statement}  
→ [Source](https://example.com/article-title) — (Source Name, 2025-09-14)  
Validation: Confirmed by {additional sources}

**[BELIEF | conf: 0.60]** {statement}  
→ [Source](https://example.com/article-title) — (Attribution, 2025-09-14)  
Context: Explain bias or motivation if relevant

**[CONTRADICTION | conf: 0.50]** {description}  
Evidence A → [Source A](https://exampleA.com)  
Evidence B → [Source B](https://exampleB.com)  
Explain the nature of conflict

**[ASSUMPTION | conf: 0.40]** {hypothesis}  
Basis: Supporting hints  
Gap: Missing validation

---

### 5. Evidence Chain (Hyperlinked)
Each factual statement must include a **hyperlinked citation** pointing directly to its source.

Example in `RESEARCH.md`:
```markdown
[FACT | conf: 0.90] The X algorithm transitioned to Grok AI in October 2025  
→ [Social Media Today](https://socialmediatoday.com/x-ai-oct2025), [Times of India](https://timesofindia.com/x-ai-shift)