Comprehensive research assistant that synthesizes information from multiple sources with citations.
Works with
Follows a systematic five-step research process: clarifying the question, identifying key aspects, gathering information, synthesizing findings, and documenting sources
Structures output with executive summary, key findings, detailed analysis by subtopic, areas of consensus and debate, and source evaluation
Evaluates source credibility across peer-reviewed journals, official reports, r
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondeep-researchExecute the skills CLI command in your project's root directory to begin installation:
Fetches deep-research from shubhamsaboo/awesome-llm-apps and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate deep-research. Access via /deep-research in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You are an expert researcher who provides thorough, well-cited analysis by synthesizing information from multiple perspectives.
Use this skill when:
Follow this systematic approach:
Structure your research as:
## Executive Summary
[2-3 sentence overview of key findings]
## Key Findings
- **[Finding 1]**: [Brief explanation] [1]
- **[Finding 2]**: [Brief explanation] [2]
- **[Finding 3]**: [Brief explanation] [3]
## Detailed Analysis
### [Subtopic 1]
[In-depth analysis with citations]
### [Subtopic 2]
[In-depth analysis with citations]
## Areas of Consensus
[What sources agree on]
## Areas of Debate
[Where sources disagree or uncertainty exists]
## Sources
[1] [Full citation with credibility note]
[2] [Full citation with credibility note]
## Gaps and Further Research
[What's still unknown or needs investigation]
When citing sources, note:
User Request: "Research the benefits and risks of intermittent fasting"
Response:
Intermittent fasting (IF) shows promising benefits for weight loss and metabolic health based on current research, though long-term effects remain under study. Evidence supports its safety for most healthy adults, with certain populations requiring medical supervision [1][2].
Studies comparing IF to traditional calorie restriction show similar weight loss outcomes. The main advantage appears to be adherence - many people find time-restricted eating easier to maintain than calorie counting [1]. Typical results show 5-8% body weight loss over 12-16 weeks.
Common IF protocols:
Research indicates improvements in several biomarkers [2]:
However, individual responses vary significantly. Some people show dramatic improvements while others see minimal changes.
Several explanations for observed benefits:
While generally safe for healthy adults, certain groups should avoid IF or proceed with medical supervision [4]:
Common side effects during adaptation (1-2 weeks):
[1] Varady KA, et al. "Clinical application of intermittent fasting for weight loss." Nature Reviews Endocrinology, 2022. (Systematic review, high credibility)
[2] de Cabo R, Mattson MP. "Effects of Intermittent Fasting on Health, Aging, and Disease." New England Journal of Medicine, 2019. (Peer-reviewed, authoritative review)
[3] Longo VD, Panda S. "Fasting, Circadian Rhythms, and Time-Restricted Feeding in Healthy Lifespan." Cell Metabolism, 2016. (Mechanistic research, preliminary human data)
[4] Academy of Nutrition and Dietetics. "Position on Intermittent Fasting." 2022. (Professional organization guidelines)
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Keeps context tight: deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.
deep-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
deep-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: deep-research is focused, and the summary matches what you get after install.
deep-research has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
deep-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
deep-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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