Low Risk

get_workspace_credits

Get the workspace's current credit balance and usage statistics. Returns: - currentBalance: remaining credits on the subscription plan - planType: subscription tier (e.g., "pro", "teams") - period: exact labelled window for every total (label, display, start, end) - periodDays: lookback window fo...

Risk signalsBulk/mass operation — affects multiple targets

Part of the Agentled server.

get_workspace_credits is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call get_workspace_credits to retrieve information from Agentled without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though get_workspace_credits only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_workspace_credits": {}
  }
}

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Get this rule live on your own Agentled server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access get_workspace_credits gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so get_workspace_credits only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the get_workspace_credits tool do? +

Get the workspace's current credit balance and usage statistics. Returns: - currentBalance: remaining credits on the subscription plan - planType: subscription tier (e.g., "pro", "teams") - period: exact labelled window for every total (label, display, start, end) - periodDays: lookback window for usage stats when applicable - usedThisPeriod: total credits consumed in the labelled period - totalExecutions: number of unique workflow executions in the period - averageCreditsPerExecution: average cost per run - recentUsage: last 20 credit deductions with execution/step context unless includeRecentUsage=false - costDrivers: optional bounded top workflows, steps, models, and apps when includeCostDrivers=true Every usage total is ledger-derived and must be shown with its period label. Use this to check if the workspace has enough credits before starting expensive workflows, or to report balance and burn rate to stakeholders.. It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_workspace_credits? +

Register the Agentled MCP server in PolicyLayer and add a rule for get_workspace_credits: 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 Agentled. Nothing to install.

What risk level is get_workspace_credits? +

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

Can I rate-limit get_workspace_credits? +

Yes. Add a rate_limit block to the get_workspace_credits 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_workspace_credits completely? +

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

get_workspace_credits is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentled tool call.

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