What makes RAGFlow notable?

2.5K downloads. Trust evidence available

How should RAGFlow be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

RAGFlow

Use for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check par...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.5k

Updated

Oct 9, 2026

Version

1.0.8

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.5K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2.5K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.8release · observed Mar 24, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s171cqxgnmkj5rqpyvv2jxqpz983g358:ragflow-skill

Install using `clawhub skill install s171cqxgnmkj5rqpyvv2jxqpz983g358:ragflow-skill` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/yingfeng/ragflow-skill before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-yingfeng-ragflow-skill/snapshot"

Documentation

CLAWHUB

150,387 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: ragflow-dataset-ingest
description: "Use for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check parse status; retrieve chunks with `search.py`; and list configured models."
metadata:
  openclaw:
    requires:
      env:
        - RAGFLOW_API_URL
        - RAGFLOW_API_KEY
      bins:
        - python3
    primaryEnv: RAGFLOW_API_KEY
---

# RAGFlow Dataset And Retrieval

Use only the bundled scripts in `scripts/`.
Prefer `--json` so returned fields can be relayed exactly.
Follow `reference.md` for all user-facing output.

## Use This Skill When

- the user wants to create, list, inspect, update, or delete RAGFlow datasets
- the user wants to upload, list, update, or delete documents in a dataset
- the user wants to start parsing, stop parsing, or check parse progress
- the user wants to retrieve chunks from one or more datasets
- the user wants to list configured RAGFlow models

## Core Workflow

1. Resolve the target dataset or document IDs first.
2. Run the matching script from `scripts/`.
3. Use `--json` unless a script only needs a simple text response.
4. Return API fields exactly; do not guess missing details.

Common commands:

```bash
python3 scripts/datasets.py list --json
python3 scripts/datasets.py info DATASET_ID --json
python3 scripts/datasets.py create "Example Dataset" --description "Quarterly reports" --json
python3 scripts/update_dataset.py DATASET_ID --name "Updated Dataset" --json
python3 scripts/upload.py DATASET_ID /path/to/file.pdf --json
python3 scripts/upload.py list DATASET_ID --json
python3 scripts/update_document.py DATASET_ID DOC_ID --name "Updated Document" --json
python3 scripts/parse.py DATASET_ID DOC_ID1 [DOC_ID2 ...] --json
python3 scripts/stop_parse_documents.py DATASET_ID DOC_ID1 [DOC_ID2 ...] --json
python3 scripts/parse_status.py DATASET_ID --json
python3 scripts/search.py "query" --json
python3 scripts/search.py "query" DATASET_ID --json
python3 scripts/search.py --dataset-ids DATASET_ID1,DATASET_ID2 --doc-ids DOC_ID1,DOC_ID2 "query" --json
python3 scripts/search.py --retrieval-test --kb-id DATASET_ID "query" --json
python3 scripts/list_models.py --json
```

## Guardrails

- For any delete action, list the exact items first and require explicit user confirmation before executing.
- Delete only by explicit dataset IDs or document IDs. If the user gives names or fuzzy descriptions, resolve IDs first.
- Upload does not start parsing. Start parsing only when the user asks for it.
- `parse.py` returns immediately after the start request; use `parse_status.py` for progress.
- For progress requests, use `parse_status.py` on the most specific scope available:
  - dataset specified: inspect that dataset
  - document IDs specified: pass `--doc-ids`
  - no dataset specified: list datasets first, then aggregate status across datasets
- If a parse status result includes `progress_msg`, surface it directly. For `FAIL`, tr

_meta.json

{
  "ownerId": "kn7dgx3cba8rzra4tshwthx0hs830fdd",
  "slug": "ragflow-skill",
  "version": "1.0.8",
  "publishedAt": 1774331740805
}

reference.md

# Output Format Reference

Style guide for consistent RAGFlow skill responses.
Apply this reference to all user-facing output for this skill.

## Format Decision Matrix

| Information Type | Format | Use Case |
|-----------------|--------|----------|
| Multiple items (3+) with attributes | **Table** | Datasets list, search results |
| Sequential steps | **Numbered List** | Upload workflow, procedures |
| Features/options | **Bullet List** | Capability overview |
| Structured data | **JSON Code Block** | API responses |
| Document content | **Quote Block** | Retrieved chunks |
| Single object properties | **Definition List** | Dataset details |
| Status | **Emoji + Text** | ✅ Done, 🟡 Running, ❌ Failed |

## Common Formats

### Tables (3+ items)
```markdown
| Dataset | Docs | Chunks | Status |
|---------|------|--------|--------|
| delete  | 4    | 53     | ✅     |
```
- Abbreviate long IDs: `abc123...`
- Use emojis for status: ✅ ❌ 🟡 ⚠️

### Bullet Lists
```markdown
- **Upload documents** to dataset
- **Start parsing** to generate chunks
```
- Start with verbs for actions
- Max 2 indent levels

### Numbered Lists
```markdown
1. Create dataset
2. Upload files
3. Start parsing
```
- Use for sequential procedures

### Status Icons
| Icon | Meaning |
|------|---------|
| ✅ | Success |
| ❌ | Failed |
| 🟡 | In Progress |
| ⚠️ | Warning |
| ⬜ | Empty |

## Response Templates

**List operations:**
```markdown
📋 **Datasets** (3 total)

| Name | ID | Status | Chunks |
|------|-----|--------|--------|
| test | abc... | ✅ | 152 |
```

**Search results:**
```markdown
🔍 **Results** (2 found)

| # | Source | Similarity | Content |
|---|--------|------------|---------|
| 1 | doc.pdf | 85% | excerpt... |
```

**Object details:**
```markdown
📊 **Dataset Details**

**ID:** `1ce917df20e411f191a984ba59bc54d9`
**Name:** delete
**Chunks:** 53
```

skill-card.md

## Description:

Use for RAGFlow dataset tasks: create, list, inspect, update, or delete datasets; upload, list, update, or delete documents; start or stop parsing; check parse status; retrieve chunks with search.py; and list configured models.

This skill is ready for commercial/non-commercial use.

## Publisher:

[yingfeng](https://clawhub.ai/user/yingfeng)

### License/Terms of Use:

MIT-0

## Use Case:

Developers and operators use this skill to manage RAGFlow knowledge bases, documents, parsing jobs, retrieval checks, and configured models from an agent workflow.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill uses a RAGFlow API key against the server configured in RAGFLOW_API_URL.

Mitigation: Install only for trusted RAGFlow servers, prefer HTTPS for remote servers, and use least-privilege API keys where possible.

Risk: Dataset and document update or delete actions can modify or remove RAGFlow content.

Mitigation: Review destructive actions carefully, list exact target items first, and proceed only with explicit dataset or document IDs after user confirmation.

## Reference(s):

- [ClawHub Skill Page](https://clawhub.ai/yingfeng/skills/ragflow-skill)
- [Publisher Profile](https://clawhub.ai/user/yingfeng)
- [Output Format Reference](artifact/reference.md)

## Skill Output:

**Output Type(s):** [text, markdown, shell commands, configuration, guidance]

**Output Format:** [Markdown, tables, JSON code blocks, and command snippets]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Relays RAGFlow API fields exactly when JSON output is used; requires RAGFLOW_API_URL, RAGFLOW_API_KEY, and python3.]

## Skill Version(s):

1.0.8 (source: server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

agents/openai.yaml

interface:
  display_name: "RAGFlow Dataset And Retrieval"
  short_description: "Manage datasets, docs, parsing, and retrieval"
  default_prompt: "Use $ragflow-dataset-ingest to manage RAGFlow datasets, documents, start or stop parsing, check parser status, and retrieve relevant chunks. For document delete or stop actions, require explicit document IDs."

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