Analyzes team activity signals (work hours, context-switching, recovery) and produces a Burnout Risk Score (1-100). Use when the user provides team workload data as JSON.
AI agents call analyze_burnout_risk to retrieve information from openGlad without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool reads workload data provided by the user and computes a diagnostic score. It performs no side effects—no state changes, no commands executed, no data deleted or modified, no financial operations. The output is a score derived from input metrics. This is a standard read/query operation used for business intelligence and diagnostics.
From the tool's definition Tool analyzes and produces a score based on input data ('Analyzes team activity signals... and produces a Burnout Risk Score'). The description contains no language indicating modification, deletion, execution of commands, or financial transactions.
Documented attack patterns abuse exactly the kind of access analyze_burnout_risk gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and openGlad, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_burnout_risk:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_burnout_risk": {}
}
}analyze_burnout_risk is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Analyzes team activity signals (work hours, context-switching, recovery) and produces a Burnout Risk Score (1-100). Use when the user provides team workload data as JSON. It is categorised as a Read tool in the openGlad MCP Server, which means it retrieves data without modifying state.
Register the openGlad MCP server in PolicyLayer and add a rule for analyze_burnout_risk: 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 openGlad. Nothing to install.
analyze_burnout_risk is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the analyze_burnout_risk 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.
Set action: deny in the PolicyLayer policy for analyze_burnout_risk. 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.
analyze_burnout_risk is provided by the openGlad MCP server (tuguberk/openglad). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from openGlad, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
13 openGlad tools catalogued and risk-classified — across an index of 43,000+ MCP servers.