Market Research Report Generator

Source: https://github.com/aipoch/medical-research-skills

Market Research Report Generator

This skill generates comprehensive market research reports based on a topic and optional requirements. It follows a strict workflow: Intent Analysis -> Decision Level Analysis -> Question Generation -> Data Collection -> Report Synthesis.

When to Use

• Use this skill when the request matches its documented task boundary.
• Use it when the user can provide the required inputs and expects a structured deliverable.
• Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

• Scope-focused workflow aligned to: Generates professional market research reports by analyzing business intent, decision levels, and conducting multi-source data retrieval (Web, PubMed, Clinical Trials).
• Packaged executable path(s): scripts/research_orchestrator.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

• Python: 3.10+. Repository baseline for current packaged skills.
• Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

cd "20260316/scientific-skills/Others/market-research-report-generator"
python -m py_compile scripts/research_orchestrator.py
python scripts/research_orchestrator.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/research_orchestrator.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/research_orchestrator.py.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Input

• topic (required): The main subject of the research (e.g., "Low-altitude economy", "Humanoid robots").
• requirements (optional): Specific focus areas or constraints.

Output

• A Markdown report containing Executive Summary, Market Overview, Competitive Landscape, Technical/Clinical Analysis, and Strategic Recommendations.

Workflow

1. Intent & Strategy Analysis

First, analyze the user's request to determine the business intent and the target audience's decision-making level.

• Intent Analysis: Classify the request into categories like Market Entry, Investment, or Product Strategy. Refer to references/intent_classification.md for guidelines.
• Decision Level: Determine if the report is for C-Level (strategic, concise), VP/Director (tactical, detailed), or R&D (technical). Refer to references/decision_level.md.

2. Core Question Generation

Based on the intent and level, generate 5-7 core questions that the research must answer.

• For Investment reports, focus on ROI, CAGR, and risks.
• For Product Strategy, focus on features, competitors, and user needs.
• For C-Level, prioritize high-level trends and financial impact.

3. Data Collection (Multi-Source)

You must collect data from multiple sources to ensure accuracy and depth. Do NOT make up data. Use the following tools:

A. General Market Search (If available)

If the environment provides a web search capability (e.g., WebSearch tool):

• Generate 3-5 distinct search queries based on the Core Questions.
• Find market size, trends, and news.

B. Clinical/Medical Search (If applicable)

If the topic is related to healthcare, medicine, or bio-tech:

• Unified Database Search: Use the provided script to query both clinicaltrials.gov and PubMed simultaneously.
  • Command: python scripts/research_orchestrator.py '["query1", "query2"]'
  • The script will return JSON data containing results from both sources.

4. Data Aggregation & Synthesis

• Review all gathered information.
• Cross-reference numbers (e.g., market size predictions) from different sources.
• Highlight conflicts or uncertainties.