get_recommendation

Get a personalized recommendation for what to do next.

SERVERCoach AI SOURCE94aharris/coach-ai

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/94aharris-coach-ai/get-recommendation.md

WHAT IT DOES

What get_recommendation does on Coach AI

AI agents call get_recommendation to retrieve information from Coach AI without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why get_recommendation is rated Low

This tool queries the system's stored user patterns and preferences to return a suggestion. It does not create, modify, delete, execute code, or move money. It is purely informational—the user must still decide whether to act on the recommendation. The most severe risk is a recommendation being unhelpful or biased, which has minimal blast radius for an AI agent. No destructive or financial operations are possible.

From the tool's definition Tool name 'get_recommendation' and description 'Get a personalized recommendation for what to do next' indicate a query/retrieval operation.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_recommendation safely

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

get_recommendation Allowed

get_recommendation is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_recommendation": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Coach AI, apply this rule, and every get_recommendation call is checked against it from then on.

FAQ

Questions about get_recommendation

What does the get_recommendation tool do? +

Get a personalized recommendation for what to do next. It is categorised as a Read tool in the Coach AI MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_recommendation? +

Register the Coach AI MCP server in PolicyLayer and add a rule for get_recommendation: 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 Coach AI. Nothing to install.

What risk level is get_recommendation? +

get_recommendation is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_recommendation? +

Yes. Add a rate_limit block to the get_recommendation 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 get_recommendation completely? +

Set action: deny in the PolicyLayer policy for get_recommendation. 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 get_recommendation? +

get_recommendation is provided by the Coach AI MCP server (94aharris/coach-ai). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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