adw.feedback

SERVERAlpineDataWorks Intelligence Server SOURCEhttps://api.alpinedataworks.com/mcp

Medium RISK CLASS

Category Write

Parameters 70 required

Recommended Rate-limitedsee the rule below

Registry record Grade C, identity unverified Pull the record →

This record as markdown: /tools/com-alpinedataworks-adw-intelligence-server/adw.feedback.md

WHAT IT DOES

What adw.feedback does on AlpineDataWorks Intelligence Server

AI agents use adw.feedback to create or update resources in AlpineDataWorks Intelligence Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AlpineDataWorks Intelligence Server environment.

Parameter	Type	Required	Description
`comments`	string	—	anything else
`agent_name`	string	—	optional: your agent/model name
`useful_products`	string	—	which product ids / domains are most useful to you?
`would_recommend`	boolean	—	would you recommend ADW to other agents/users?
`pricing_feedback`	string	—	is the pricing (Free / Gold $199 / Platinum $499) fair, high, or low? why?
`product_feedback`	string	—	what would make the intelligence objects more useful?
`consumable_rating`	integer	—	1-5: how easy is the data to consume in your workflow?

Parameters from the server's own tool schema.

RISK

Why adw.feedback is rated Medium

The tool collects and submits survey feedback to an external server. Submitting answers is a Write operation (creates a new record). There are no destructive, financial, or execution-level effects. Misuse risk is low — an AI agent could submit inaccurate or misleading feedback, but the blast radius is minimal.

From the tool's definition 'call again WITH answers to submit' — submitting survey responses creates data on the server side; questions cover product usefulness, pricing, and recommendations

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs adw.feedback safely

PolicyLayer is an MCP gateway: it sits between your AI agents and AlpineDataWorks Intelligence Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For adw.feedback, this is the rule to start with:

adw.feedback Rate-limited

adw.feedback stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "adw.feedback": {
      "limits": [
        {
          "counter": "adw.feedback_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect AlpineDataWorks Intelligence Server, apply this rule, and every adw.feedback call is checked against it from then on.

FAQ

Questions about adw.feedback

What does the adw.feedback tool do? +

We'd love your feedback as an AI agent using this data. Call with NO arguments to see the short survey; call again WITH answers to submit. Helps us make the data more agent-consumable. Questions: is the data easy to consume? which products are useful? is the pricing fair? would you recommend it?. It is categorised as a Write tool in the AlpineDataWorks Intelligence Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does adw.feedback accept? +

adw.feedback accepts 7 parameters: comments, agent_name, useful_products, would_recommend, pricing_feedback, product_feedback, consumable_rating. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on adw.feedback? +

Register the AlpineDataWorks Intelligence Server MCP server in PolicyLayer and add a rule for adw.feedback: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AlpineDataWorks Intelligence Server. Nothing to install.

What risk level is adw.feedback? +

adw.feedback is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit adw.feedback? +

Yes. Add a rate_limit block to the adw.feedback rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block adw.feedback completely? +

Set action: deny in the PolicyLayer policy for adw.feedback. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides adw.feedback? +

adw.feedback is provided by the AlpineDataWorks Intelligence Server MCP server (https://api.alpinedataworks.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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