---
name: Grant Proposal Builder
slug: grant-proposal-builder
category: Writing
description: Grant Proposal Builder drafts structured funding applications from research ideas and literature. Use it when turning a validated project into agency-specific proposals such as KAKENHI, NSF, NSFC, or ERC.
github: "https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-grant-proposal"
language: JavaScript
stars: 1047
forks: 116
install: "npx degit https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-grant-proposal ~/.claude/skills/aris-grant-proposal"
installs_to: ~/.claude/skills/aris-grant-proposal
source_path: skills/aris-grant-proposal/SKILL.md
collection_size: 25
category_size: 1012
collection_url: "https://dirskills.com/collections/OpenLAIR/dr-claw"
added: 2026-08-21T05:14:01.328Z
last_synced: 2026-08-21T05:14:01.328Z
canonical_url: "https://dirskills.com/skills/grant-proposal-builder"
---

# Grant Proposal Builder

Grant Proposal Builder drafts structured funding applications from research ideas and literature. Use it when turning a validated project into agency-specific proposals such as KAKENHI, NSF, NSFC, or ERC.

**Install:**

```bash
npx degit https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-grant-proposal ~/.claude/skills/aris-grant-proposal
```

## README

# Grant Proposal: From Research Ideas to Fundable Application

Draft a grant proposal based on: **$ARGUMENTS**

## Overview

This skill turns validated research ideas into a structured, reviewer-ready grant proposal. It chains sub-skills into a grant-specific pipeline:

```
/aris-research-lit → /aris-novelty-check → [structure design] → [draft] → /aris-research-review → [revise] → GRANT_PROPOSAL.md
  (survey)      (verify gap)     (aims + matrix)     (prose)    (panel review)     (fix)      (done!)
```

**This is a parallel branch, not part of the linear Workflow 1→1.5→2→3 pipeline.** After `/aris-idea-discovery` produces validated ideas, the user can either:
- Go to `/aris-experiment-bridge` → `/aris-auto-review-loop` → `/aris-paper-writing` (implement & publish)
- Go to `/aris-grant-proposal` (write funding application first, then implement after funding)

```
                    ┌→ /aris-experiment-bridge → /aris-auto-review-loop → /aris-paper-writing  (publish track)
/aris-idea-discovery ────┤
                    └→ /aris-grant-proposal → [get funded] → /aris-experiment-bridge → ...  (funding track)
```

Grant proposals argue for **future work** (feasibility + potential), not completed work (results + claims). This skill handles the unique requirements of grant writing: narrative arc design, reviewer-facing structure, budget justification, timeline planning, and agency-specific formatting.

## Constants

- **GRANT_TYPE = `KAKENHI`** — Default grant type. Supported: `KAKENHI`, `NSF`, `NSFC`, `ERC`, `DFG`, `SNSF`, `ARC`, `NWO`, `GENERIC`. Override via argument (e.g., `/aris-grant-proposal "topic — NSF"`).
- **GRANT_SUBTYPE = `auto`** — Sub-type within the grant agency. Examples: KAKENHI `Start-up`/`Wakate`/`Kiban-B`; NSFC `Youth`/`Excellent-Youth`/`Distinguished`/`Overseas`/`Key`; NSF `CAREER`/`CRII`/`Standard`. Auto-detected from argument or defaults to the most common sub-type.
- **REVIEWER_MODEL = `gpt-5.4`** — Model used via Codex MCP for proposal review. Must be an OpenAI model (e.g., `gpt-5.4`, `o3`, `gpt-4o`).
- **OUTPUT_FORMAT = `markdown`** — Output format. Supported: `markdown`, `latex`. LaTeX uses grant-specific templates when available.
- **MAX_REVIEW_ROUNDS = 2** — Maximum external review-revise cycles before finalizing.
- **OUTPUT_DIR = `grant-proposal/`** — Directory for generated proposal files.
- **LANGUAGE = `auto`** — Output language. Auto-detected from grant type: KAKENHI→Japanese, NSF→English, NSFC→Chinese, ERC→English, DFG→English (or German), SNSF→English, ARC→English, NWO→English. Override explicitly if needed.
- **AUTO_PROCEED = false** — At each checkpoint, **always wait for explicit user confirmation** before proceeding. Grant proposals require PI-specific judgment at every stage. Set `true` only if user explicitly requests fully autonomous mode.

> 💡 These are defaults. Override by telling the skill, e.g., `/aris-grant-proposal "topic — NSF CAREER, latex output"` or `/aris-grant-proposal "topic — NSFC Youth, language: English"`.

## Grant Type Specifications

### KAKENHI (Japan — JSPS)

| Field | Detail |
|-------|--------|
| **Sections** | 研究目的 (Research Objective), 研究計画・方法 (Plan & Methods), 準備状況 (Preparation Status), 人権の保護 (Ethics, if applicable) |
| **Sub-types** | 基盤研究 A/B/C (Kiban), 若手研究 (Wakate), 研究活動スタート支援 (Start-up), 国際共同研究 (International), 学術変革領域 (Transformative), 挑戦的研究 (Challenging), DC1/DC2 (doctoral) |
| **Language** | Japanese (English technical terms acceptable) |
| **Review criteria** | 学術的重要性 (academic significance), 独創性 (originality), 研究計画の妥当性 (plan feasibility), 研究遂行能力 (PI capability) |
| **Cultural norms** | Explicit yearly milestones (Year 1 / Year 2), budget justification integrated into plan, emphasize 社会的意義 (societal significance), concrete expected outputs (papers, datasets), reference KAKEN database for related funded projects |

### NSF (US)

| Field | Detail |
|-------|--------|
| **Sections** | Project Summary (1p), Project Description (15p max), References Cited, Biographical Sketch, Budget Justification, Data Management Plan |
| **Sub-types** | Standard Grant, CAREER (early career), CRII (research initiation), RAPID, EAGER |
| **Language** | English |
| **Review criteria** | Intellectual Merit, Broader Impacts |
| **Cultural norms** | Aim-based structure (Aim 1/2/3), preliminary data strongly expected, broader impacts must be concrete and specific (not generic "benefit society"), Results from Prior Support section |

### NSFC (China — 国家自然科学基金)

| Field | Detail |
|-------|--------|
| **Sections** | 立项依据 (Rationale & Significance), 研究内容 (Content), 研究目标 (Objectives), 研究方案 (Plan & Methods), 可行性分析 (Feasibility), 创新性 (Innovation Points), 预期成果 (Expected Outcomes), 研究基础 (PI Foundation & Track Record) |
| **Sub-types** | 面上项目 (General Program) — emphasis on scientific problem and research accumulation; 青年基金 (Young Scientists Fund) — age ≤35, emphasis on independence and growth potential; 优秀青年基金/优青 (Excellent Young Scientists) — age ≤38, emphasis on outstanding achievements; 杰出青年基金/杰青 (Distinguished Young Scientists) — age ≤45, emphasis on international-leading level; 海外优青 (Overseas Excellent Young Scientists) — emphasis on overseas experience and return contribution plan; 重点项目 (Key Program) — emphasis on systematic in-depth research |
| **Language** | Chinese |
| **Review criteria** | 科学意义 (scientific significance), 创新性 (innovation), 可行性 (feasibility), 研究队伍 (team qualification) |
| **Cultural norms** | Heavy emphasis on 国际前沿 (international frontier) positioning, detailed feasibility analysis, explicit citation of applicant's prior publications, 研究基础 section is critical for demonstrating PI capability |

### ERC (EU — European Research Council)

| Field | Detail |
|-------|--------|
| **Sections** | Extended Synopsis (5p), Scientific Proposal Part B2 (15p) |
| **Sub-types** | Starting Grant (2-7 years post-PhD), Consolidator Grant (7-12 years), Advanced Grant (established leaders) |
| **Language** | English |
| **Review criteria** | Ground-breaking nature, Methodology, PI track record |
| **Cultural norms** | Emphasis on "high-risk/high-gain", methodology table with WP/deliverables/milestones, Gantt chart expected, strong PI narrative |

### DFG (Germany — Deutsche Forschungsgemeinschaft)

| Field | Detail |
|-------|--------|
| **Sections** | State of the Art, Objectives, Work Programme, Bibliography, CV |
| **Language** | English or German |
| **Review criteria** | Scientific quality, Originality, Feasibility, PI qualification |

### SNSF (Switzerland — Swiss National Science Foundation)

| Field | Detail |
|-------|--------|
| **Sections** | Summary, Research Plan, Timetable, Budget |
| **Language** | English |
| **Review criteria** | Scientific relevance, Originality, Feasibility, Track record |

### ARC (Australia — Australian Research Council)

| Field | Detail |
|-------|--------|
| **Sections** | Project Description, Feasibility, Benefit, Budget |
| **Language** | English |
| **Review criteria** | Research quality, Feasibility, Benefit to Australia |

### NWO (Netherlands — Dutch Research Council)

| Field | Detail |
|-------|--------|
| **Sections** | Summary, Proposed Research, Knowledge Utilisation |
| **Language** | English |
| **Review criteria** | Scientific quality, Innovative character, Knowledge utilisation |

### GENERIC

For any grant not listed above. User provides section names, page limits, and review criteria via argument:

```
/aris-grant-proposal "topic — GENERIC, sections: Background|Methods|Impact, language: English"
```

## State Persistence (Compact Recovery)

Grant proposal drafting is a long task that may trigger context compaction. Persist state to `grant-proposal/GRANT_STATE.json` after each phase:

```json
{
  "phase": 2,
  "grant_type": "KAKENHI",
  "grant_subtype": "Start-up",
  "language": "Japanese",
  "codex_thread_id": "019cfcf4-...",
  "gap_statement": "...",
  "aims_count": 3,
  "status": "in_progress",
  "timestamp": "2026-03-18T15:00:00"
}
```

**Write this file at the end of every phase.** On invocation, check for this file:
- If absent or `status: "completed"` → fresh start
- If `status: "in_progress"` and within 24h → **resume** from saved phase (read `GRANT_PROPOSAL.md` and `GRANT_REVIEW.md` to restore context)
- If older than 24h → fresh start (stale state)

On completion, set `"status": "completed"`.

## Workflow

### Phase 0: Input Parsing & Context Gathering

Parse `$ARGUMENTS` to extract:

1. **Research direction/idea** — may reference existing files or be a freeform description
2. **Grant type** — detect from keywords (e.g., "科研費"→KAKENHI, "NSF"→NSF, "国自然"→NSFC, "基金"→NSFC)
3. **Grant sub-type** — detect from keywords (e.g., "Start-up", "若手", "青年", "CAREER", "优青", "海外优青")
4. **Overrides** — output format, language, review rounds

Then gather context from the project directory:

1. Read `IDEA_REPORT.md` if it exists (from `/aris-idea-discovery`)
2. Read `refine-logs/FINAL_PROPOSAL.md` if it exists (from `/aris-research-refine`)
3. Read `refine-logs/EXPERIMENT_PLAN.md` if it exists (from `/aris-experiment-plan`)
4. Read `AUTO_REVIEW.md` if it exists (from `/aris-auto-review-loop` — prior review feedback is gold for grants)
5. Read `NARRATIVE_REPORT.md` or `STORY.md` if they exist
6. Read any existing literature notes or survey documents
7. Scan for the user's publication list (e.g., `publications.md`, `cv.md`, `bio.md`, `CV.pdf`)
8. Check for `grant-proposal/GRANT_STATE.json` (resume from prior interrupted run)

If insufficient context exists:
- No research idea at all → suggest running `/aris-idea-discovery` first
- No literature survey → will invoke `/aris-research-lit` inline in Phase 1
- No publication list → leave PI qualification section with `[TODO: Add publications]` placeholders
- Has AUTO_REVIEW.md → extract reviewer feedback and use it to strengthen the feasibility narrative

### Phase 1: Literature & Landscape Positioning

Invoke `/aris-research-lit` to ground the proposal in real literature, then search for competing funded projects:

```
/aris-research-lit "$ARGUMENTS"
```

**What this does:**
- Reuse existing surveys if `/aris-research-lit` was already run and notes exist
- Otherwise invoke `/aris-research-lit` for multi-source literature search (arXiv, Scholar, Zotero, local PDFs)
- Search for **funded projects** in the same area via WebSearch:
  - KAKENHI → KAKEN database (https://kaken.nii.ac.jp/)
  - NSF → NSF Award Search (https://www.nsf.gov/awardsearch/)
  - NSFC → NSFC funded projects
  - Other agencies → general web search
- Identify competing groups and their recent publications
- Run `/aris-novelty-check` on the proposed research direction to verify the gap is real:
  ```
  /aris-novelty-check "[proposed gap statement]"
  ```
- Build the **gap statement** — the single most important sentence in the proposal:
  ```
  "Despite progress in [X], [specific gap] remains unaddressed because [reason].
  This proposal addresses this by [approach], which will [expected impact]."
  ```

**🚦 Checkpoint:** Present the landscape summary and gap statement to the user:

```
📚 Literature & landscape analysis complete:
- [key findings from literature]
- [competing funded projects found]
- Gap statement: "[the gap statement]"

Does this accurately capture the positioning? Should I adjust before designing the proposal structure?
```

**⛔ STOP HERE and wait for user response.** Do NOT auto-proceed unless AUTO_PROCEED=true was explicitly set by the user.

Options for the user:
- Reply **"go"** or **"ok"** → proceed to Phase 2 with current positioning
- Reply with **adjustments** (e.g., "focus more on X", "the gap should emphasize Y") → refine and re-present
- Reply **"stop"** → end the skill, save current progress to `grant-proposal/DRAFT_NOTES.md`

**State**: Write `GRANT_STATE.json` with `phase: 1` and the gap statement.

### Phase 2: Narrative Structure & Aims Design

Design the proposal's logical architecture before writing any prose.

#### 2.1 Define Specific Aims (2-4)

Each aim must satisfy:
- **Independently valuable** — if one aim fails, others still produce publishable results
- **Logically connected** — Aim 1 enables Aim 2, Aim 2 informs Aim 3
- **Concrete deliverables** — each aim maps to specific outputs (papers, datasets, tools, benchmarks)
- **Feasible within budget and timeline**

#### 2.2 Build Claims-Aims-Evidence Matrix

```markdown
| Aim | Key Claim | Preliminary Evidence | Proposed Validation | Risk Level | Deliverable |
|-----|-----------|---------------------|--------------------|-----------:|-------------|
| Aim 1 | [claim] | [pilot data, prior work] | [experiments] | LOW | [paper, dataset] |
| Aim 2 | [claim] | [theoretical basis] | [experiments] | MEDIUM | [paper, tool] |
```

#### 2.3 Design the Narrative Arc

Grant proposals follow a fundamentally different arc from papers:

```
Problem → Why Now → What We Propose → Why It Will Work → What We Will Deliver
         (not: Problem → Method → Results → Implications)
```

- **Problem**: What gap exists and why it matters (scientific + societal)
- **Why Now**: What recent developments make this the right time (new data, new methods, new need)
- **What We Propose**: The specific aims and approach
- **Why It Will Work**: Preliminary data, PI track record, team expertise, feasibility arguments
- **What We Will Deliver**: Concrete outputs, timeline, expected publications

#### 2.4 Timeline & Milestones

Design year-by-year (or quarter-by-quarter) plan:

```markdown
### Year 1
- Q1-Q2: [Aim 1 tasks]
- Q3-Q4: [Aim 1 completion + Aim 2 start]
- Expected outputs: [papers, datasets]

### Year 2
- Q1-Q2: [Aim 2 completion + Aim 3]
- Q3-Q4: [Aim 3 completion + synthesis]
- Expected outputs: [papers, tools, final report]
```

#### 2.5 Structural Review

Invoke `/aris-research-review` to get critical feedback on the proposal structure before drafting:

```
/aris-research-review "[GRANT_TYPE] [GRANT_SUBTYPE] proposal structure:
Gap: [gap statement]
Aims: [aims list with claims-evidence matrix]
Timeline: [timeline]
— reviewer persona: [GRANT_TYPE] review panelist"
```

**What this does:**
- GPT-5.4 xhigh acts as a grant review panelist (not a paper reviewer)
- Evaluates aims independence, narrative arc, risk identification, timeline realism
- Identifies the single biggest reviewer concern
- Provides actionable fixes ranked by severity

Apply structural feedback before proceeding to drafting.

**🚦 Checkpoint:** Present the proposal structure to the user:

```
🏗️ Proposal structure designed:
- Gap: [gap statement]
- Aim 1: [title] — Risk: LOW
- Aim 2: [title] — Risk: MEDIUM
- Aim 3: [title] — Risk: LOW
- Timeline: [summary]
- Reviewer feedback: [key points from GPT-5.4]

Proceed to section drafting? Or adjust the structure?
```

**⛔ STOP HERE. This is the most critical checkpoint — the proposal structure determines everything downstream.**

Options for the user:
- Reply **"go"** or **"ok"** → proceed to Phase 3 (section drafting)
- Reply with **structural changes** (e.g., "merge Aim 2 and 3", "add an aim about X", "reduce to 2 aims") → redesign and re-present
- Reply **"back"** → return to Phase 1 to adjust the gap/positioning
- Reply **"stop"** → save current structure to `grant-proposal/DRAFT_NOTES.md`

**State**: Write `GRANT_STATE.json` with `phase: 2`, aims summary, and Codex threadId.

### Phase 3: Section Drafting

Draft each section according to the grant type template. Write **complete prose**, not outlines or placeholders.

**What this does:**
- Writes all required sections in the agency-specific language and tone
- Pulls content from IDEA_REPORT.md, FINAL_PROPOSAL.md, and literature notes
- Uses `/aris-paper-illustration` for figure generation (if user requests)
- Leaves `[TODO]` only for PI-specific information, `[AMOUNT]` for budget figures
- Outputs `grant-proposal/GRANT_PROPOSAL.md`

#### Drafting Order (optimized for narrative coherence)

1. **Specific Aims / Research Objective** — the "abstract" of the grant. Write first, refine last.
2. **Background / Significance / State of the Art** — establish the problem and gap.
3. **Research Plan / Methods** — per aim, with feasibility arguments.
4. **Figures** — generate key diagrams (see below).
5. **Timeline & Milestones** — year-by-year deliverables.
6. **PI Qualification / Preparation Status** — track record, team, infrastructure.
7. **Budget Justification** — narrative only (leave dollar/yen amounts as `[AMOUNT]` placeholders).
8. **Broader Impacts / Societal Significance** — if required by the grant type.

#### Figure Generation

Grant proposals benefit greatly from clear diagrams. Generate the following figures using SVG or matplotlib (save to `grant-proposal/figures/`):

1. **全体構成図 / Overview Diagram** — Show the relationship between aims (Aim 1 → Aim 2 → Aim 3), shared resources (participants, stimuli, pipeline), and outputs. This is the single most important figure.
2. **実験パラダイム図 / Experimental Paradigm** — Visual schematic of each paradigm (stimulus timing, conditions, EEG recording).
3. **年次計画 / Timeline Gantt Chart** — Year-by-year (or H1/H2) milestones with deliverables.

For AI-generated publication-quality figures, invoke `/aris-paper-illustration`:

```
/aris-paper-illustration "Overview diagram showing [aims relationship + shared resources] for grant proposal"
```

For simpler diagrams (flowcharts, Gantt charts), generate clean SVG or matplotlib directly via code.

**🚦 Figure Checkpoint:** Before generating, ask which figures the user wants:

```
🎨 The following figures would strengthen this proposal:
1. 全体構成図 / Overview — aims relationship + shared resources
2. 実験パラダイム図 / Paradigm — stimulus timing + conditions
3. 年次計画 / Gantt — timeline with milestones

Which should I generate? (e.g., "1 and 3", "all", "skip")
```

**⛔ Wait for user response.** Generate only the requested figures.

#### Grant-Specific Drafting Guidelines

**KAKENHI:**
- Write in formal Japanese academic style (である調, not です/ます調)
- Use 「」for Japanese quotations, bold for emphasis
- Structure: 研究の学術的背景 → 研究期間内に何をどこまで明らかにするか → 本研究の学術的な特色・独創性
- Include explicit 年次計画 (yearly plan) with concrete milestones
- Emphasize 社会的意義 (societal significance)
- Reference related KAKEN-funded projects to show awareness of the field

**NSF:**
- Write in clear, direct English
- Use Aim-based structure with bold headings
- Preliminary data paragraphs for each Aim (with figure references)
- Broader Impacts must be concrete: specific outreach activities, broadening participation plans
- Include Results from Prior Support (if PI has prior NSF funding)

**NSFC:**
- Write in formal Chinese academic style
- 立项依据 must position work at 国际前沿 (international frontier)
- 创新性 section must list numbered innovation points (创新点)
- 研究基础 must cite PI's own publications (with IF and citations if possible)
- 可行性分析 must address: technical feasibility, team capability, time feasibility, equipment/conditions

**ERC:**
- Write a compelling "high-risk/high-gain" narrative
- Extended Synopsis must be self-contained and compelling
- Include Work Package table with deliverables and milestones
- Gantt chart (describe in text, or generate as figure)

#### For Each Section

1. **Pull relevant content** from IDEA_REPORT.md, FINAL_PROPOSAL.md, literature notes
2. **Write complete prose** — no `[TODO]` except for PI-specific information
3. **Include figure/table placeholders** where appropriate (e.g., `[Figure 1: System architecture]`)
4. **Cite references properly** — use citation keys, will build bibliography later
5. **Match the agency's tone and style** — formal Japanese for KAKENHI, direct English for NSF, etc.

### Phase 4: External Review

Invoke `/aris-research-review` on the complete draft for grant-type-specific evaluation:

```
/aris-research-review "Complete [GRANT_TYPE] [GRANT_SUBTYPE] proposal draft. Evaluate as a [GRANT_TYPE] review panelist using official criteria. [PASTE FULL PROPOSAL TEXT]"
```

**What this does:**
- GPT-5.4 xhigh acts as a