# Assess Seed Industry Data Assets

Seed data projects face complex germplasm, ownership, important-data, and approval requirements. This skill structures assessments and assetization plans before valuation or RWA work begins.

## Install

```bash
npx skillstore add 图灵数盟/dhturing-seed-industry-data-asset-expert
```

## Metadata

- Status: approved
- Slug: dhturing-seed-industry-data-asset-expert
- Skillstore revision: r1
- Version status: missing
- Tree hash: d9575990f6721fe81265a11dbbda360e67b57f8977ef82c410d6ae02407e6e93
- Author: 图灵数盟
- GitHub username: dhturing
- License: MIT
- Repository: https://github.com/dhturing/turing-data-experts/tree/9c58ffa97ec5b760befef6f910eb23107cdcdbf4/skills/seed-industry-data-asset-expert
- Ref: 50b73f83991cf073cbdf3f5afad2bbac71dd3bae
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: filesystem, external\_commands, network
- Quality score: 77
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/dhturing-seed-industry-data-asset-expert
- Manifest: https://skillstore.pages.dev/api/skills/dhturing-seed-industry-data-asset-expert/manifest

## Capabilities

- Classifies breeding, genomic, weather, soil, machinery, and traceability data by asset characteristics.
- Checks germplasm, variety approval, genetically modified organism, and important-data compliance gates.
- Maps contributions, rights, authorizations, and benefit allocation across farmers, cooperatives, platforms, and breeders.
- Designs data aggregation, quality, lineage, desensitization, registration, and delivery workflows.
- Structures valuation and RWA planning for eligible varieties, datasets, and data income rights.
- Produces assessment tables, compliance checklists, ownership plans, SOPs, and quality controls.

## Use Cases

- Screen Cooperative Data: Classify farm and breeding datasets, identify missing authorizations, and determine whether assetization can proceed.
- Plan Breeding Data Registration: Separate variety rights from data rights and prepare a registration and valuation work plan.
- Evaluate Agricultural RWA Readiness: Review compliance gates, ownership evidence, important-data exposure, and proposed income-right structures.

## Prompt Templates

### Classify My Seed Data

```
Classify these datasets as breeding, genomic, weather, soil, machinery, or traceability data. Explain each asset characteristic and required evidence: [dataset inventory].
```

### Run a Compliance Screening

```
Assess this project for germplasm, variety approval, genetically modified organism, important-data, personal-information, and cross-border concerns: [project details]. Return proceed, remediate, or stop.
```

### Design an Ownership Plan

```
Map data contributions and rights for farmers, cooperatives, platforms, and breeders. Propose required authorizations, benefit allocation, evidence, and unresolved decisions: [stakeholders and contracts].
```

### Build an Assetization and RWA Roadmap

```
Create a phased roadmap from compliance review through data processing, registration, valuation, and RWA assessment. Include deliverables, dependencies, stop conditions, quality checks, and responsible parties: [project dossier].
```

## Limitations

- Does not grant variety approval, germplasm approval, or other administrative authorization.
- Does not replace licensed appraisers, lawyers, financial institutions, or data exchanges.
- Policy references require verification against current regulator publications and local rules.
- Cannot determine ownership or value without project evidence, contracts, data inventories, and approval records.

## Best Practices

- Provide a complete data inventory, stakeholder map, contracts, approvals, processing history, and intended use.
- Verify current laws, regulator guidance, and local registration rules before relying on any recommendation.
- Treat compliance gates and written authorization as prerequisites for valuation, registration, financing, or RWA planning.

## Anti Patterns

- Do not treat germplasm, variety rights, and data rights as the same legal asset.
- Do not estimate value or promote financing without evidence, assumptions, and sensitivity analysis.
- Do not share precise agricultural locations, genomic data, or personal information before classification and authorization.

## Security Audit

- Audited at: 2026-09-27T03:12:16.987\+00:00
- Summary: All 13 static findings are false positives caused by Markdown syntax, documented installation paths, public website links, and high-entropy heuristics on Chinese text. The reviewed files contain no executable commands, hidden-file operations, encoded payloads, or prompt-injection attempts.

## Stats

- Views: 0
- Downloads: 1
- Favorites: 0
- Popularity score: 0