research-grants

K-Dense-AI/scientific-agent-skills · updated Jun 4, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill research-grants
0 commentsdiscussion
summary

### Research Grants

  • name: "research-grants"
  • description: "Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation na..."
  • allowed-tools: "Read Write Edit Bash"
skill.md
name
research-grants
description
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
allowed-tools
Read Write Edit Bash
license
MIT license
compatibility
Works in Agent Skills-compatible hosts. Grant-writing guidance needs no network; optional figures via the scientific-schematics skill require OPENROUTER_API_KEY and outbound API access.
metadata
version: "1.1" skill-author: K-Dense Inc.

Research Grant Writing

Overview

Research grant writing is the process of developing competitive funding proposals for federal agencies and foundations. Master agency-specific requirements, review criteria, narrative structure, budget preparation, and compliance for NSF (National Science Foundation), NIH (National Institutes of Health), DOE (Department of Energy), DARPA (Defense Advanced Research Projects Agency), and Taiwan's NSTC (National Science and Technology Council) submissions.

Critical Principle: Grants are persuasive documents that must simultaneously demonstrate scientific rigor, innovation, feasibility, and broader impact. Each agency has distinct priorities, review criteria, formatting requirements, and strategic goals that must be addressed.

When to Use This Skill

This skill should be used when:

  • Writing research proposals for NSF, NIH, DOE, DARPA, or NSTC programs
  • Preparing project descriptions, specific aims, or technical narratives
  • Developing broader impacts or significance statements
  • Creating research timelines and milestone plans
  • Preparing budget justifications and personnel allocation plans
  • Responding to program solicitations or funding announcements
  • Addressing reviewer comments in resubmissions
  • Planning multi-institutional collaborative proposals
  • Writing preliminary data or feasibility sections
  • Preparing biosketches, CVs, or facilities descriptions

Visual Enhancement (Optional)

Strong proposals often include 1–3 figures (timelines, workflow diagrams, preliminary data). Figures support review but are not a substitute for clear aims and methods.

When figures help:

  • Research methodology and workflow diagrams
  • Project timeline or Gantt charts
  • Conceptual framework or system architecture (technical proposals)
  • Experimental design flowcharts
  • Broader impacts activity diagrams
  • NSTC CM03 research architecture diagrams (often expected)

How to create figures:

  • Preferred: Use the scientific-schematics skill (--doc-type grant) for AI-generated diagrams from a natural-language description
  • Alternative: Build figures in your usual tools (matplotlib, Illustrator, PowerPoint, etc.)

From the scientific-schematics skill directory, with OPENROUTER_API_KEY set:

python scripts/generate_schematic.py "project timeline with Year 1-3 milestones" -o figures/timeline.png --doc-type grant

Disclosure: AI schematic generation sends your prompt to OpenRouter (a third-party API). Do not include unpublished sensitive details unless that transmission is appropriate for your project.


Agency-Specific Overview

NSF (National Science Foundation)

Mission: Promote the progress of science and advance national health, prosperity, and welfare

Key Features:

  • Follow PAPPG 24-1 (effective May 20, 2024) unless a solicitation overrides it
  • Intellectual Merit + Broader Impacts (equally weighted)
  • 15-page project description limit (most programs; includes Results from Prior NSF Support, max 5 pages)
  • Emphasis on education, diversity, and societal benefit
  • Collaborative research encouraged
  • Open data and open science emphasis
  • Merit review process with panel + ad hoc reviewers

NIH (National Institutes of Health)

Mission: Enhance health, lengthen life, and reduce illness and disability

Key Features:

  • Specific Aims (1 page) + Research Strategy (12 pages for R01)
  • Significance, Innovation, Approach as core review criteria
  • Preliminary data typically required for R01s
  • Emphasis on rigor, reproducibility, and clinical relevance
  • Modular budgets ($250K increments) for most R01s
  • Multiple resubmission opportunities

DOE (Department of Energy)

Mission: Ensure America's security and prosperity through energy, environmental, and nuclear challenges

Key Features:

  • Focus on energy, climate, computational science, basic energy sciences
  • Often requires cost sharing or industry partnerships
  • Emphasis on national laboratory collaboration
  • Strong computational and experimental integration
  • Energy innovation and commercialization pathways
  • Varies by office (ARPA-E, Office of Science, EERE, etc.)

DARPA (Defense Advanced Research Projects Agency)

Mission: Make pivotal investments in breakthrough technologies for national security

Key Features:

  • High-risk, high-reward transformative research
  • Focus on "DARPA-hard" problems (what if true, who cares)
  • Emphasis on prototypes, demonstrations, and transition paths
  • Often requires multiple phases (feasibility, development, demonstration)
  • Strong project management and milestone tracking
  • Teaming and collaboration often required
  • Varies dramatically by program manager and BAA (Broad Agency Announcement)

NSTC (National Science and Technology Council - Taiwan)

Mission: Advance scientific breakthrough, industrial application, and societal impact in Taiwan.

Key Features:

  • CM03 Form: The core technical proposal format.
  • Bilingual: Abstract required in both Chinese and English.
  • Innovation & Feasibility: Primary review focus.
  • Preliminary Data: Highly critical for credibility.
  • Research Architecture Diagram: A mandatory visual element for clarity.

Core Components of Research Proposals

1. Executive Summary / Project Summary / Abstract

Every proposal needs a concise overview that communicates the essential elements of the research to both technical reviewers and program officers.

Purpose: Provide a standalone summary that captures the research vision, significance, and approach

Length:

  • NSF: 1 page (Project Summary with separate Overview, Intellectual Merit, Broader Impacts)
  • NIH: 30 lines (Project Summary/Abstract)
  • DOE: Varies (typically 1 page)
  • DARPA: Varies (often 1-2 pages)

Essential Elements:

  • Clear statement of the problem or research question
  • Why this problem matters (significance, urgency, impact)
  • Novel approach or innovation
  • Expected outcomes and deliverables
  • Qualifications of the team
  • Broader impacts or translational pathway

Writing Strategy:

  • Open with a compelling hook that establishes importance
  • Use accessible language (avoid jargon in opening sentences)
  • State specific, measurable objectives
  • Convey enthusiasm and confidence
  • Ensure every sentence adds value (no filler)
  • End with transformative vision or impact statement

Common Mistakes to Avoid:

  • Being too technical or detailed (save for project description)
  • Failing to articulate "why now" or "why this team"
  • Vague objectives or outcomes
  • Neglecting broader impacts or significance
  • Generic statements that could apply to any proposal

2. Project Description / Research Strategy

The core technical narrative that presents the research plan in detail.

Structure Varies by Agency:

NSF Project Description (typically 15 pages):

  • Introduction and background
  • Research objectives and questions
  • Preliminary results (if applicable)
  • Research plan and methodology
  • Timeline and milestones
  • Broader impacts (integrated throughout or separate section)
  • Prior NSF support (if applicable)

NIH Research Strategy (12 pages for R01):

  • Significance (why the problem matters)
  • Innovation (what's novel and transformative)
  • Approach (detailed research plan)
    • Preliminary data
    • Research design and methods
    • Expected outcomes
    • Potential problems and alternative approaches

DOE Project Narrative (varies):

  • Background and significance
  • Technical approach and innovation
  • Qualifications and experience
  • Facilities and resources
  • Project management and timeline

DARPA Technical Volume (varies):

  • Technical challenge and innovation
  • Approach and methodology
  • Schedule and milestones
  • Deliverables and metrics
  • Team qualifications
  • Risk assessment and mitigation

For detailed agency-specific guidance, refer to:

  • references/nsf_guidelines.md
  • references/nih_guidelines.md
  • references/doe_guidelines.md
  • references/darpa_guidelines.md
  • references/nstc_guidelines.md

3. Specific Aims (NIH) or Objectives (NSF/DOE/DARPA)

Clear, testable goals that structure the research plan.

NIH Specific Aims Page (1 page):

  • Opening paragraph: Gap in knowledge and significance
  • Long-term goal and immediate objectives
  • Central hypothesis or research question
  • 2-4 specific aims with sub-aims
  • Expected outcomes and impact
  • Payoff paragraph: Why this matters

Structure for Each Aim:

  • Aim statement (1-2 sentences, starts with action verb)
  • Rationale (why this aim, preliminary data support)
  • Working hypothesis (testable prediction)
  • Approach summary (brief methods overview)
  • Expected outcomes and interpretation

Writing Strategy:

  • Make aims independent but complementary
  • Ensure each aim is achievable within timeline and budget
  • Provide enough detail to judge feasibility
  • Include contingency plans or alternative approaches
  • Use parallel structure across aims
  • Clearly state what will be learned from each aim

For detailed guidance, refer to references/specific_aims_guide.md.

4. Broader Impacts (NSF) / Significance (NIH)

Articulate the societal, educational, or translational value of the research.

NSF Broader Impacts (critical component, equal weight with Intellectual Merit):

NSF explicitly evaluates broader impacts. Address at least one of these areas:

  1. Advancing discovery and understanding while promoting teaching, training, and learning

    • Integration of research and education
    • Training of students and postdocs
    • Curriculum development
    • Educational materials and resources
  2. Broadening participation of underrepresented groups

    • Recruitment and retention strategies
    • Partnerships with minority-serving institutions
    • Outreach to underrepresented communities
    • Mentoring programs
  3. Enhancing infrastructure for research and education

    • Shared facilities or instrumentation
    • Cyberinfrastructure and data resources
    • Community-wide tools or databases
    • Open-source software or methods
  4. Broad dissemination to enhance scientific and technological understanding

    • Public outreach and science communication
    • K-12 educational programs
    • Museum exhibits or media engagement
    • Policy briefs or stakeholder engagement
  5. Benefits to society

    • Economic impact or commercialization
    • Health, environment, or national security benefits
    • Informed decision-making
    • Workforce development

Writing Strategy for NSF Broader Impacts:

  • Be specific with concrete activities, not vague statements
  • Provide timeline and milestones for broader impacts activities
  • Explain how impacts will be measured and assessed
  • Connect to institutional resources and existing programs
  • Show commitment through preliminary efforts or partnerships
  • Integrate with research plan (not tacked on)

NIH Significance:

  • Addresses important problem or critical barrier to progress
  • Improves scientific knowledge, technical capability, or clinical practice
  • Potential to lead to better outcomes, interventions, or understanding
  • Rigor of prior research in the field
  • Alignment with NIH mission and institute priorities

For detailed guidance, refer to references/broader_impacts.md.

5. Innovation and Transformative Potential

Articulate what is novel, creative, and paradigm-shifting about the research.

Innovation Elements to Highlight:

  • Conceptual Innovation: New frameworks, models, or theories
  • Methodological Innovation: Novel techniques, approaches, or technologies
  • Integrative Innovation: Combining disciplines or approaches in new ways
  • Translational Innovation: New pathways from discovery to application
  • Scale Innovation: Unprecedented scope or resolution

Writing Strategy:

  • Clearly state what is innovative (don't assume it's obvious)
  • Explain why current approaches are insufficient
  • Describe how your innovation overcomes limitations
  • Provide evidence that innovation is feasible (preliminary data, proof-of-concept)
  • Distinguish incremental from transformative advances
  • Balance innovation with feasibility (not too risky)

Common Mistakes:

  • Claiming novelty without demonstrating knowledge of prior work
  • Confusing "new to me" with "new to the field"
  • Over-promising without supporting evidence
  • Being too incremental (minor variation on existing work)
  • Being too speculative (no path to success)

6. Research Approach and Methods

Detailed description of how the research will be conducted.

Essential Components:

  • Overall research design and framework
  • Detailed methods for each aim/objective
  • Sample sizes, statistical power, and analysis plans
  • Timeline and sequence of activities
  • Data collection, management, and analysis
  • Quality control and validation approaches
  • Potential problems and alternative strategies
  • Rigor and reproducibility measures

Writing Strategy:

  • Provide enough detail for reproducibility and feasibility assessment
  • Use subheadings and figures to improve organization
  • Justify choice of methods and approaches
  • Address potential limitations proactively
  • Include preliminary data demonstrating feasibility
  • Show that you've thought through the research process
  • Balance detail with readability (use supplementary materials for extensive details)

For Experimental Research:

  • Describe experimental design (controls, replicates, blinding)
  • Specify materials, reagents, and equipment
  • Detail data collection protocols
  • Explain statistical analysis plans
  • Address rigor and reproducibility

For Computational Research:

  • Describe algorithms, models, and software
  • Specify datasets and validation approaches
  • Explain computational resources required
  • Address code availability and documentation
  • Describe benchmarking and performance metrics

For Clinical or Translational Research:

  • Describe study population and recruitment
  • Detail intervention or treatment protocols
  • Explain outcome measures and assessments
  • Address regulatory approvals (IRB, IND, IDE)
  • Describe clinical trial design and monitoring

7. Preliminary Data and Feasibility

Demonstrate that the research is achievable and the team is capable.

Purpose:

  • Prove that the proposed approach can work
  • Show that the team has necessary expertise
  • Demonstrate access to required resources
  • Reduce perceived risk for reviewers
  • Provide foundation for proposed work

What to Include:

  • Pilot studies or proof-of-concept results
  • Method development or optimization
  • Access to unique resources (samples, data, collaborators)
  • Relevant publications from your team
  • Preliminary models or simulations
  • Feasibility assessments or power calculations

NIH Requirements:

  • R01 applications typically require substantial preliminary data
  • R21 applications may have less stringent requirements
  • New investigators may have less preliminary data
  • Preliminary data should directly support proposed aims

NSF Approach:

  • Preliminary data less commonly required than NIH
  • May be important for high-risk or novel approaches
  • Can strengthen proposal for competitive programs

Writing Strategy:

  • Present most compelling data that supports your approach
  • Clearly connect preliminary data to proposed aims
  • Acknowledge limitations and how proposed work will address them
  • Use figures and data visualizations effectively
  • Avoid over-interpreting or overstating preliminary findings
  • Show trajectory of your research program

8. Timeline, Milestones, and Management Plan

Demonstrate that the project is well-planned and achievable within the proposed timeframe.

Essential Elements:

  • Phased timeline with clear milestones
  • Logical sequence and dependencies
  • Realistic timeframes for each activity
  • Decision points and go/no-go criteria
  • Risk mitigation strategies
  • Resource allocation across time
  • Coordination plan for multi-institutional teams

Presentation Formats:

  • Gantt charts showing overlapping activities
  • Year-by-year breakdown of activities
  • Quarterly milestones and deliverables
  • Table of aims/tasks with timeline and personnel

Writing Strategy:

  • Be realistic about what can be accomplished
  • Build in time for unexpected delays or setbacks
  • Show that timeline aligns with budget and personnel
  • Demonstrate understanding of regulatory timelines (IRB, IACUC)
  • Include time for dissemination and broader impacts
  • Address how progress will be monitored and assessed

DARPA Emphasis:

  • Particularly important for DARPA proposals
  • Clear technical milestones with measurable metrics
  • Quarterly deliverables and reporting
  • Phase-based structure with exit criteria
  • Demonstration and transition planning

9. Team Qualifications and Collaboration

Demonstrate that the team has the expertise, experience, and resources to succeed.

Essential Elements:

  • PI qualifications and relevant expertise
  • Co-I and collaborator roles and contributions
  • Track record in the research area
  • Complementary expertise across team
  • Institutional support and resources
  • Prior collaboration history (if applicable)
  • Mentoring and training plan (for students/postdocs)

Writing Strategy:

  • Highlight most relevant publications and accomplishments
  • Clearly define roles and responsibilities
  • Show that team composition is necessary (not just convenient)
  • Demonstrate successful prior collaborations
  • Address how team will be managed and coordinated
  • Explain institutional commitment and support

Biosketches / CVs:

  • Follow agency-specific formats (NSF, NIH, DOE, DARPA differ)
  • Highlight most relevant publications and accomplishments
  • Include synergistic activities and collaborations
  • Show trajectory and productivity
  • Address any career gaps or interruptions

Letters of Collaboration:

  • Specific commitments and contributions
  • Demonstrates genuine partnership
  • Includes resource sharing or access agreements
  • Signed and on letterhead

10. Budget and Budget Justification

Develop realistic budgets that align with the proposed work and agency guidelines.

Budget Categories (typical):

  • Personnel: Salary and fringe for PI, co-Is, postdocs, students, staff
  • Equipment: Items >$5,000 (varies by agency)
  • Travel: Conferences, collaborations, fieldwork
  • Materials and Supplies: Consumables, reagents, software
  • Other Direct Costs: Publication costs, participant incentives, consulting
  • Indirect Costs (F&A): Institutional overhead (rates vary)
  • Subawards: Costs for collaborating institutions

Agency-Specific Considerations:

NSF:

  • Full budget justification required
  • Cost sharing generally not required (but may strengthen proposal)
  • Up to 2 months summer salary for faculty
  • Graduate student support encouraged

NIH:

  • Modular budgets for ≤$250K direct costs per year (R01)
  • Detailed budgets for >$250K or complex awards
  • Salary cap: Executive Level II (updated annually; see NIH Salary Cap Summary) — e.g., $228,000 effective January 1, 2026 (NOT-OD-26-034); cap applies to direct and indirect salaries for awards issued on or after October 1, 2024 (NOT-OD-25-025)
  • Limited to 1 month (8.33% FTE) for most PIs

DOE:

  • Often requires cost sharing (especially ARPA-E)
  • Detailed budget with quarterly breakdown
  • Requires institutional commitment letters
  • National laboratory collaboration budgets separate

DARPA:

  • Detailed budgets by phase and task
  • Requires supporting cost data for large procurements
  • Often requires cost-plus or firm-fixed-price structures
  • Travel budget for program meetings

Budget Justification Writing:

  • Justify each line item in terms of the research plan
  • Explain effort percentages for personnel
  • Describe specific equipment and why necessary
  • Justify travel (conferences, collaborations)
  • Explain consultant roles and rates
  • Show how budget aligns with timeline

Review Criteria by Agency

Understanding how proposals are evaluated is critical for writing competitive applications.

NSF Review Criteria

Intellectual Merit (primary):

  • What is the potential for the proposed activity to advance knowledge?
  • How well-conceived and organized is the proposed activity?
  • Is there sufficient access to resources?
  • How well-qualified is the individual, team, or institution to conduct proposed activities?

Broader Impacts (equally important):

  • What is the potential for the proposed activity to benefit society?
  • To what extent does the proposal address broader impacts in meaningful ways?

Additional Considerations:

  • Integration of research and education
  • Diversity and inclusion
  • Results from prior NSF support (if applicable)

NIH Review Criteria

Scored Criteria (1-9 scale, 1 = exceptional, 9 = poor):

  1. Significance

    • Addresses important problem or critical barrier
    • Improves scientific knowledge, technical capability, or clinical practice
    • Aligns with NIH mission
  2. Investigator(s)

    • Well-suited to the project
    • Track record of accomplishments
    • Adequate training and expertise
  3. Innovation

    • Novel concepts, approaches, methodologies, or interventions
    • Challenges existing paradigms
    • Addresses important problem in creative ways
  4. Approach

    • Well-reasoned and appropriate
    • Rigorous and reproducible
    • Adequately accounts for potential problems
    • Feasible within timeline
  5. Environment

    • Institutional support and resources
    • Scientific environment contributes to probability of success

Additional Review Considerations (not scored but discussed):

  • Protections for human subjects
  • Inclusion of women, minorities, and children
  • Vertebrate animal welfare
  • Biohazards
  • Resubmission response (if applicable)
  • Budget and timeline appropriateness

DOE Review Criteria

Varies by program office, but generally includes:

  • Scientific and/or technical merit
  • Appropriateness of proposed method or approach
  • Competency of personnel and adequacy of facilities
  • Reasonableness and appropriateness of budget
  • Relevance to DOE mission and program goals

DARPA Review Criteria

DARPA-specific considerations:

  • Overall scientific and technical merit
  • Potential contribution to DARPA mission
  • Realism of proposed costs and availability of funds

Frame proposals with DARPA-style impact questions when appropriate:

  • What if you succeed? — Impact if the research works
  • What if you're right? — Implications of your hypothesis
  • Who cares? — Why it matters for national security

NSTC Review Criteria

Core Evaluation Dimensions:

  1. Innovation (創新性): Novelty of concept and approach.
  2. Feasibility (可行性): Methodology rigor and preliminary data.
  3. PI Capability (主持人能力): Track record and expertise.
  4. Value (價值): Academic contribution and societal/industrial impact.

For detailed review criteria, refer to references/nstc_guidelines.md.

Writing Princip

how to use research-grants

How to use research-grants 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 development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add research-grants
2

Execute installation command

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

$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill research-grants

The skills CLI fetches research-grants from GitHub repository K-Dense-AI/scientific-agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/research-grants

Reload or restart Cursor to activate research-grants. Access the skill through slash commands (e.g., /research-grants) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.535 reviews
  • Neel Martin· Dec 28, 2024

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

  • Ira Khan· Dec 28, 2024

    We added research-grants from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Min Yang· Dec 24, 2024

    research-grants is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Dhruvi Jain· Dec 12, 2024

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

  • Jin Agarwal· Nov 19, 2024

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

  • Ishan Huang· Nov 19, 2024

    research-grants fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Nov 3, 2024

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

  • Ganesh Mohane· Oct 22, 2024

    We added research-grants from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Jin Ndlovu· Oct 10, 2024

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

  • Jin Mensah· Oct 10, 2024

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

showing 1-10 of 35

1 / 4