# Send Grago to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "grago",
    "name": "Grago",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/solsuk/grago",
    "canonicalUrl": "https://clawhub.ai/solsuk/grago",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/grago",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=grago",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "README.md",
      "SECURITY.md",
      "SKILL.md",
      "grago.sh",
      "install.sh"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "grago",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-05-04T00:14:03.214Z",
      "expiresAt": "2026-05-11T00:14:03.214Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=grago",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=grago",
        "contentDisposition": "attachment; filename=\"grago-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "grago"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/grago"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/grago",
    "downloadUrl": "https://openagent3.xyz/downloads/grago",
    "agentUrl": "https://openagent3.xyz/skills/grago/agent",
    "manifestUrl": "https://openagent3.xyz/skills/grago/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/grago/agent.md"
  }
}
```
## Documentation

### Grago

Delegate research and data-fetch tasks to a free local LLM. Save tokens. Use your machine.

Grago bridges the gap between your OpenClaw agent and local LLMs (Ollama, llama.cpp, etc.) that can't use tools natively. It runs shell scripts to fetch live data from the web, APIs, and local files — then pipes the results into your local model with a focused prompt.

Your cloud model stays sharp. Your local machine does the grunt work. Your token bill drops.

### ⚠️ Security Model

Grago executes shell commands. This is intentional — it's the only way to give tool-less local LLMs access to external data.

Safe for: Trusted, single-user environments (your own Mac Mini, VPS, workstation)
NOT safe for: Multi-tenant systems, public APIs, untrusted agents

If your OpenClaw agent is compromised via prompt injection, Grago can execute arbitrary commands. This is the trade-off for free local compute. Read SECURITY.md in the repo for full details.

### When to Use This Skill

Use Grago when:

You need live data fetched (web pages, APIs, RSS feeds, logs)
The task is research-heavy and doesn't need your primary model
You want to keep data on your own machine (privacy)
You want to save tokens by offloading analysis to a local LLM

### How It Works

Fetch — Shell scripts pull live data (curl, jq, grep, etc.)
Analyze — Results are piped to your local Ollama model with a prompt
Return — Structured analysis comes back to your OpenClaw agent

### Usage

# Fetch a URL and analyze locally
grago fetch "https://example.com" \\
  --analyze "Summarize the key points" \\
  --model gemma2

# Multi-source research from a YAML config
grago research \\
  --sources sources.yaml \\
  --prompt "What are the main themes across these sources?"

# Pipe any shell command into your local model
grago pipe \\
  --fetch "curl -s https://api.example.com/data" \\
  --transform "jq .results" \\
  --analyze "Identify trends and flag outliers"

### Configuration

Config file: ~/.grago/config.yaml

default_model: gemma2        # Your preferred Ollama model
timeout: 30                  # Seconds per fetch
max_input_chars: 16000       # Input truncation limit
output_format: markdown      # markdown | json | text

### Requirements

Ollama installed and running locally (install.sh handles this)
At least one model pulled in Ollama (gemma2, mistral, llama3, etc.)
bash, curl, jq

### Installation

git clone https://github.com/solsuk/grago.git
cd grago && ./install.sh

### Notes for the Agent

Prefer pipe mode over fetch --analyze for reliability (avoids Ollama TTY spinner issues)
Default model is whatever is set in ~/.grago/config.yaml; override per-call with --model
Input is truncated to max_input_chars before being sent to the local model
Local model responses can be slow (5–30s depending on hardware and model size) — this is expected
Grago is for research and fetch delegation — not for tasks requiring your primary model's reasoning
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: solsuk
- Version: 1.0.1
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-05-04T00:14:03.214Z
- Expires at: 2026-05-11T00:14:03.214Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/grago)
- [Send to Agent page](https://openagent3.xyz/skills/grago/agent)
- [JSON manifest](https://openagent3.xyz/skills/grago/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/grago/agent.md)
- [Download page](https://openagent3.xyz/downloads/grago)