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academic-deep-research

Trigger this skill when the user wants:

kesslerio/academic-deep-research-clawhub-skillUpdated Jun 21, 2026

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/kesslerio/academic-deep-research-clawhub-skill --skill academic-deep-research

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this week

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Installation Guide

How to use academic-deep-research on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your machine
  • ›Node.js 16+ with npm — verify with node --version
  • ›Active project directory where you want to add academic-deep-research
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/kesslerio/academic-deep-research-clawhub-skill --skill academic-deep-research

Fetches academic-deep-research from kesslerio/academic-deep-research-clawhub-skill and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/academic-deep-research

Restart Cursor to activate academic-deep-research. Access via /academic-deep-research in your agent's command palette.

⚠

Security Notice

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.

›View source on GitHub›Skills CLI docs›About Cursor›What are agent skills?

Documentation

Academic Deep Research 🔬

When to Use

Trigger this skill when the user wants:

  • Deep research, exhaustive analysis, or literature review
  • Multi-source verification and evidence hierarchies
  • Academic-style reports with citations

Required Stop Points

  1. Initial engagement: ask 2–3 clarifying questions and confirm understanding.
  2. Research plan: present themes, steps, and deliverables; wait for approval.
  3. Final report: deliver full narrative report with citations.

Minimum Requirements

  • Two full research cycles per theme.
  • Analyze between every tool call.
  • Multiple sources per claim; contradictions addressed.
  • APA 7th in-text citations and reference list.
  • Narrative-only final report (no lists or tables).

References

  • reference/protocol.md — research phases, tool order, and analysis rules
  • reference/writing-style.md — narrative constraints and phase formatting
  • reference/citations-apa.md — citation rules and examples
  • reference/report-template.md — required report structure
  • reference/error-handling.md — gaps, contradictions, failures
  • reference/quality-standards.md — evidence hierarchy and confidence levels
  • reference/parallel-research.md — sessions_spawn workflow
  • quickref.md — short checklist
  • example.md — sample usage

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • ›Claude Desktop or compatible AI client
  • ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • ›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Steps

  1. 1Install product management skill
  2. 2Start with user story generation for known feature
  3. 3Progress to competitive analysis: research 2-3 competitors
  4. 4Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5Draft stakeholder communications and refine based on feedback
  6. 6Build template library for recurring PM tasks
  7. 7Share effective prompts with product team

Common Pitfalls

  • ⚠Not validating competitive research—verify facts before sharing
  • ⚠Accepting user stories without involving engineering team
  • ⚠Over-relying on frameworks without qualitative judgment
  • ⚠Not customizing outputs to company culture and communication style
  • ⚠Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • −Don't publish competitive analysis without fact-checking
  • −Don't finalize user stories without engineering review
  • −Don't make prioritization decisions solely on AI scoring
  • −Don't skip customer validation of generated requirements
  • −Don't ignore company-specific context and culture

💡 Pro Tips

  • ★Provide context: company goals, constraints, customer feedback
  • ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • ★Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

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Reviews

4.5★★★★★67 reviews
  • H
    Hassan Patel★★★★★Dec 28, 2024

    Useful defaults in academic-deep-research — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • A
    Anika Lopez★★★★★Dec 24, 2024

    academic-deep-research has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • A
    Ava Sharma★★★★★Dec 24, 2024

    Registry listing for academic-deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.

  • A
    Aisha Farah★★★★★Dec 24, 2024

    academic-deep-research reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • A
    Ama Torres★★★★★Dec 8, 2024

    Keeps context tight: academic-deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • G
    Ganesh Mohane★★★★★Dec 4, 2024

    Registry listing for academic-deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.

  • M
    Mia Huang★★★★★Nov 27, 2024

    Registry listing for academic-deep-research matched our evaluation — installs cleanly and behaves as described in the markdown.

  • S
    Sakshi Patil★★★★★Nov 23, 2024

    Keeps context tight: academic-deep-research is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • A
    Aisha Nasser★★★★★Nov 19, 2024

    I recommend academic-deep-research for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • W
    William Okafor★★★★★Nov 15, 2024

    Solid pick for teams standardizing on skills: academic-deep-research is focused, and the summary matches what you get after install.

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