# my_tool

A other tool on the Agentic Automl Platform MCP server.

Agent View of the PolicyLayer registry record for `my_tool`. HTML page: https://policylayer.com/tools/agentic-automl-platform/my-tool

## Facts

- Tool: `my_tool`
- Server: Agentic Automl Platform (`anantshri1/agentic-automl-platform`) — https://policylayer.com/tools/agentic-automl-platform.md
- Homepage: https://github.com/anantshri1/agentic-automl-platform
- Risk category: Other (Low risk)
- Registry record: grade C, identity unverified
- Server rate-limited: no
- Parameters: 0
- Recommended policy verdict: Rate-limited

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "my_tool",
    "arguments": {}
  }
}
```

## Why my_tool is rated Low

With no description and a generic placeholder name, it is impossible to determine what this tool does. Given the sibling tools relate to ML workflows (training, evaluation, data cleaning), it could be a read or write operation, but there is insufficient evidence to classify it confidently. Defaulting to 'Other' with very low confidence due to complete lack of information.

From the tool's own definition: "Tool name is 'my_tool' with an empty description, providing no information about its function or effects."

## Use case

AI agents call my_tool as a supporting operation in Agentic Automl Platform workflows.

## Recommended policy (PolicyLayer)

Verdict: **Rate-limited**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Agentic Automl Platform:

```json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "my_tool": {
      "limits": [
        {
          "counter": "my_tool_rate",
          "window": "minute",
          "max": 60,
          "scope": "grant"
        }
      ]
    }
  }
}
```

## Other tools on Agentic Automl Platform (13)

- `evaluate_ffn` — Execute — https://policylayer.com/tools/agentic-automl-platform/evaluate-ffn.md
- `hyperparameter_search` — Execute — https://policylayer.com/tools/agentic-automl-platform/hyperparameter-search.md
- `train_ffn` — Execute — https://policylayer.com/tools/agentic-automl-platform/train-ffn.md
- `train_lstm` — Execute — https://policylayer.com/tools/agentic-automl-platform/train-lstm.md
- `train_model` — Execute — https://policylayer.com/tools/agentic-automl-platform/train-model.md
- `train_transformer` — Execute — https://policylayer.com/tools/agentic-automl-platform/train-transformer.md
- `check_class_balance` — Read — https://policylayer.com/tools/agentic-automl-platform/check-class-balance.md
- `detect_problem_type` — Read — https://policylayer.com/tools/agentic-automl-platform/detect-problem-type.md
- `evaluate_model` — Read — https://policylayer.com/tools/agentic-automl-platform/evaluate-model.md
- `prepare_forecast_dataset` — Read — https://policylayer.com/tools/agentic-automl-platform/prepare-forecast-dataset.md
- `profile_dataset` — Read — https://policylayer.com/tools/agentic-automl-platform/profile-dataset.md
- `clean_dataset` — Write — https://policylayer.com/tools/agentic-automl-platform/clean-dataset.md
- `reduce_dimensions` — Write — https://policylayer.com/tools/agentic-automl-platform/reduce-dimensions.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=agentic-automl-platform · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/agentic-automl-platform