Low Risk

time_patterns

Analyse when pollution is highest — hour of day, day of week, and month. Returns temporal profiles showing typical patterns. Useful for advising on best times for outdoor exercise, school runs, or commuting. Args: location: Postcode, place name, or "lat,lon". pollutant: Pollutant to analyse — "NO...

Part of the Hermes — Air Quality Intelligence server.

time_patterns 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 time_patterns to retrieve information from Hermes — Air Quality Intelligence 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 time_patterns 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": {
    "time_patterns": {}
  }
}

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Get this rule live on your own Hermes — Air Quality Intelligence 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 time_patterns 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 time_patterns 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 time_patterns tool do? +

Analyse when pollution is highest — hour of day, day of week, and month. Returns temporal profiles showing typical patterns. Useful for advising on best times for outdoor exercise, school runs, or commuting. Args: location: Postcode, place name, or "lat,lon". pollutant: Pollutant to analyse — "NO2", "PM2.5", "PM10", "O3" (default "NO2"). period: Time window — "last_month", "last_3_months", "last_6_months", or "last_year" (default).. It is categorised as a Read tool in the Hermes — Air Quality Intelligence MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on time_patterns? +

Register the Hermes — Air Quality Intelligence MCP server in PolicyLayer and add a rule for time_patterns: 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 Hermes — Air Quality Intelligence. Nothing to install.

What risk level is time_patterns? +

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

Can I rate-limit time_patterns? +

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

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

time_patterns is provided by the Hermes — Air Quality Intelligence MCP server (https://hermes.southlondonscientific.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Hermes — Air Quality Intelligence tool call.

Deterministic rules across all 15 Hermes — Air Quality Intelligence tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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