Low Risk

log_event

Log a completion or a re-watch/re-read/re-listen with a date. Use when the user mentions finishing something again ("watched Heat again last night", "reread Dune"). The first finish is tracked by status; this records repeats so they show in history and stats.

Part of the Achriom server.

log_event 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 log_event to retrieve information from Achriom 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 log_event 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": {
    "log_event": {}
  }
}

See the full Achriom policy for all 33 tools.

Get this rule live on your own Achriom 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 log_event gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so log_event 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 log_event tool do? +

Log a completion or a re-watch/re-read/re-listen with a date. Use when the user mentions finishing something again ("watched Heat again last night", "reread Dune"). The first finish is tracked by status; this records repeats so they show in history and stats.. It is categorised as a Read tool in the Achriom MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on log_event? +

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

What risk level is log_event? +

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

Can I rate-limit log_event? +

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

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

log_event is provided by the Achriom MCP server (https://mcp.achriom.com/mcp?api_key={api_key}). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Achriom tool call.

Deterministic rules across all 33 Achriom tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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