dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
Research technical projects/papers and generate comprehensive reports with PDF export. Modes: lite (analysis + writing) or full (+ environment setup + experiments). Params: iterations, mode, project-path, output. Use for paper analysis, code review, technical reports, research documentation.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install huaruoji/research-reportExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Analyze technical projects/papers and produce comprehensive reports with PDF export.
bash {baseDir}/scripts/research-report.sh \
--topic "Spatial Forcing" \
--mode lite \
--iterations 3 \
--output both
| Parameter | Default | Description |
|---|---|---|
--topic |
(required) | Paper/project name or arXiv ID |
--mode |
lite |
lite or full |
--iterations |
3 |
Report revision iterations |
--output |
both |
md, pdf, or both |
--project-path |
(auto) | Local code directory (optional) |
--workspace |
(current) | Workspace directory |
--project-path provided)<workspace>/
├── reports/
│ ├── <topic>_report_v1.md
│ ├── <topic>_report_v2.md
│ ├── <topic>_report_final.md
│ └── <topic>_report_final.pdf
├── memory/YYYY-MM-DD.md (appended)
└── logs/<topic>_research.log
The generated report follows this structure:
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# Research Report Generator
Analyze technical projects/papers and produce comprehensive reports with PDF export.
## Modes
### Lite Mode (default)
- Literature search + paper analysis
- Code reading (local or remote)
- Multi-iteration report writing
- PDF generation via md2pdf skill
- **No environment setup or experiment runs**
### Full Mode
- Everything in lite mode +
- Conda/virtualenv setup
- Dependency installation
- Experiment execution
- Result analysis
## Usage
```bash
bash {baseDir}/scripts/research-report.sh \
--topic "Spatial Forcing" \
--mode lite \
--iterations 3 \
--output both
```
## Parameters
| Parameter | Default | Description |
|-----------|---------|-------------|
| `--topic` | (required) | Paper/project name or arXiv ID |
| `--mode` | `lite` | `lite` or `full` |
| `--iterations` | `3` | Report revision iterations |
| `--output` | `both` | `md`, `pdf`, or `both` |
| `--project-path` | (auto) | Local code directory (optional) |
| `--workspace` | (current) | Workspace directory |
## Workflow
### Phase 1: Discovery
1. Search arXiv + project pages
2. Fetch related papers (citations + references)
3. Identify key technologies and dependencies
### Phase 2: Analysis
1. Read source code (if `--project-path` provided)
2. Analyze architecture from docs/code
3. Map technology stack
### Phase 3: Report Writing (× iterations)
1. Draft outline
2. Write sections iteratively
3. Add diagrams (Mermaid/ASCII)
4. Refine explanations
### Phase 4: Export (Full mode only)
1. Setup conda env
2. Install dependencies
3. Run experiments
4. Append results to report
### Phase 5: PDF Generation
1. Call md2pdf skill
2. Send to user via Telegram
## Output Structure
```
<workspace>/
├── reports/
│ ├── <topic>_report_v1.md
│ ├── <topic>_report_v2.md
│ ├── <topic>_report_final.md
│ └── <topic>_report_final.pdf
├── memory/YYYY-MM-DD.md (appended)
└── logs/<topic>_research.log
```
## Report Template
The generated report follows this structure:
1. **Ex...University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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