Copyright (c) 2026 The State Key Laboratory of Blockchain and Data Security, Zhejiang University SPDX-License-Identifier: Apache-2.0 -->
Scanned 9/12/2026
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---
name: guixu-data-agent
description: "Copyright (c) 2026 The State Key Laboratory of Blockchain and Data Security, Zhejiang University SPDX-License-Identifier: Apache-2.0 -->"
category: ai-agents-and-harness
source_repo: hashgraph-online/awesome-codex-plugins
source_path: "plugins/guixu-project/guixu/skills/guixu/SKILL.md"
source_url: https://github.com/hashgraph-online/awesome-codex-plugins/blob/HEAD/plugins/guixu-project/guixu/skills/guixu/SKILL.md
---
<!--
Copyright (c) 2026 The State Key Laboratory of Blockchain and Data Security, Zhejiang University
SPDX-License-Identifier: Apache-2.0
-->
---
name: guixu
description: "Dataset discovery, valuation, and acquisition for AI training. Use when: (1) finding datasets for model training or fine-tuning, (2) evaluating dataset quality and relevance, (3) downloading datasets from Kaggle, HuggingFace, IPFS, or other sources, (4) assessing dataset licensing and provenance, (5) acquiring paid or free datasets. NOT for: generic web search (use browser), local file operations (use file tools), or data labeling/annotation tasks."
metadata:
{
"openclaw":
{
"emoji": "📊",
"requires": { "bins": ["guixu"] },
"install":
[
{
"id": "brew",
"kind": "brew",
"formula": "guixu",
"bins": ["guixu"],
"label": "Install Guixu CLI (brew)",
},
],
},
}
---
# Guixu Data Agent
Guixu provides dataset discovery, valuation, and acquisition for AI agents.
It searches across Kaggle, HuggingFace, IPFS, arXiv, DBLP, and other sources.
## When to Use
✅ **USE this skill when:**
- User asks to "find a dataset for training..."
- User asks to "download a dataset about..."
- User asks to "evaluate dataset quality..."
- User asks about dataset licensing or provenance
- User mentions specific datasets (Kaggle, HuggingFace, etc.)
- User wants to search for training data
❌ **DON'T use this skill when:**
- Generic web search → use browser or web search tools
- Local file read/write → use file tools
- Data labeling or annotation → use coding tools
- Code implementation questions → use coding-agent skill
## Workflow
### Step 1: Parse Intent (REQUIRED first)
Always start with `intent_parse` to structure the request:
```
intent_parse(query="find me a cat image dataset for classification", task_type="classification")
```
This returns a structured `QueryProfile` with:
- `task_type`: classification, detection, segmentation, etc.
- `keywords`: dataset content terms
- `target_entity`: main subject
- `data_standard`: sample_unit, budget, schema expectations
### Step 2: Search Datasets
Use `dataset_search` with keywords from intent_parse:
```
dataset_search(query="cat image", task_type="classification", limit=10)
```
Supported sources (leave empty to search all):
- `kaggle`, `huggingface`, `ipfs`, `bittorrent`
- `arxiv`, `dblp`, `semanticscholar`
- `defillama`, `rwa_xyz`, `guixu-hub`
- `pansearch` (cloud drives)
Filter options:
- `filters.max_price`: maximum price in USD
- `filters.free_only`: only free datasets
- `filters.license`: specific license (e.g., "CC-BY-4.0")
### Step 3: Evaluate Candidates
For each promising candidate, call `dataset_evaluate`:
```
dataset_evaluate(cid="kaggle:owner/dataset-name", task_description="cat image classification", task_type="classification", required_columns=["image_path", "label"])
```
This returns:
- `tcv_score`: -100 (harmful) to +100 (highly valuable)
- `schema_fit`: compatibility with required columns
- `community_signal`: reviews and ratings
### Step 4: Download
Once a dataset is selected:
```
dataset_download(cid="kaggle:owner/dataset-name")
# or
dataset_download(cid="hf:owner/dataset-name")
```
Free sources: `uci:`, `openml:`, `zenodo:`, `figshare:`, `hf:` (public), `ipfs:`, `guixu-hub:`
Requires login: `kaggle:`
## Tool Chaining Examples
### Classification Dataset
```
1. intent_parse(query="find me a dog vs cat classification dataset", task_type="classification")
2. dataset_search(query="cat dog classification", task_type="classification", limit=10)
3. dataset_evaluate(cid="kaggle:username/dataset", task_description="dog cat binary classification", task_type="classification", required_columns=["image_path", "label"])
4. dataset_download(cid="kaggle:username/dataset")
```
### Detection Dataset
```
1. intent_parse(query="find helmet detection dataset with bounding boxes", task_type="detection")
2. dataset_search(query="helmet detection bounding box", task_type="detection", limit=10)
3. For each candidate: dataset_evaluate(cid, task_description="helmet detection", task_type="detection", required_columns=["image_path", "bbox"])
4. Download best candidate
```
### Tabular Finance Dataset
```
1. intent_parse(query="find stock price dataset for time series forecasting", task_type="forecasting")
2. dataset_search(query="stock price time series", task_type="forecasting", filters={source: "defillama"})
3. dataset_evaluate(cid, task_description="stock price prediction", task_type="forecasting", required_columns=["timestamp", "price"])
4. dataset_download(cid)
```
## Important Notes
- **Always call `intent_parse` FIRST** — it extracts task_type and keywords that improve search quality
- **Keywords should be CONTENT only** — no task words like "classification" or "detection"
- **Check license before purchase** — use `require_license_review: true` in evaluation
- **Budget enforcement** — set `filters.max_price` or `budget` to limit spending
- **Free sources first** — try `guixuhub`, `huggingface`, `ipfs` before paid sources
## Error Handling
If `dataset_search` returns no results:
- Try broader keywords
- Remove source filters
- Check if the source is spelled correctly
If `dataset_evaluate` fails:
- Dataset may be unavailable
- Try a different candidate
If `dataset_download` fails:
- Check if login is required (Kaggle)
- Verify the CID format is correct: `source:owner/dataset`
---
**Source:** [`hashgraph-online/awesome-codex-plugins`](https://github.com/hashgraph-online/awesome-codex-plugins) → `plugins/guixu-project/guixu/skills/guixu/SKILL.md`
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