NIH funding trend analysis to identify high-priority research areas.
⚠️ Note: This is a demonstration/illustrative version using mock data for educational purposes. For production use, integration with real funding databases (NIH RePORTER, NSF Award Search, etc.) is required.
Analyze funding patterns to guide research strategy.
scripts/main.py.references/ for task-specific guidance.See ## Prerequisites above for related details.
Python: 3.10+. Repository baseline for current packaged skills.Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.cd "20260318/scientific-skills/Evidence Insight/grant-funding-scout"
python -m py_compile scripts/main.py
python scripts/main.py --help
Example run plan:
CONFIG block or documented parameters if the script uses fixed settings.python scripts/main.py with the validated inputs.See ## Workflow above for related details.
scripts/main.py.references/ contains supporting rules, prompts, or checklists.Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --help
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
--research-area | str | Yes | - | Research field to analyze (e.g., "cancer immunotherapy") |
--years | int | No | 3 | Analysis time window in years |
--output | str | No | stdout | Output file path for results |
--format | str | No | json | Output format: json, csv, or text |
--top-n | int | No | 10 | Number of top results to display |
Input: "cancer immunotherapy", years=3 Output: Funding increased 40% YoY; CAR-T and checkpoint inhibitors dominate
Current Version: Uses mock funding data for demonstration purposes.
For Production Use:
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
No additional Python packages required.
Every final response should make these items explicit when they are relevant:
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.This skill accepts requests that match the documented purpose of grant-funding-scout and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
grant-funding-scoutonly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Use the following fixed structure for non-trivial requests:
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.