Low Risk

query_frontier

Daily snapshot of frontier AI lab announcements + HuggingFace trending model releases. Sources: OpenAI / DeepMind / Meta / Mistral blog RSS, Anthropic + HF blogs (via shared rss corpus), and the HF trending models API. Use when a user asks "what model dropped" or "did <lab> announce X".

Risk signalsAccepts freeform code/query input (query)

Part of the Fillin server.

query_frontier 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 query_frontier to retrieve information from Fillin 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 query_frontier 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": {
    "query_frontier": {}
  }
}

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Get this rule live on your own Fillin 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 query_frontier 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 query_frontier 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 query_frontier tool do? +

Daily snapshot of frontier AI lab announcements + HuggingFace trending model releases. Sources: OpenAI / DeepMind / Meta / Mistral blog RSS, Anthropic + HF blogs (via shared rss corpus), and the HF trending models API. Use when a user asks "what model dropped" or "did <lab> announce X".. It is categorised as a Read tool in the Fillin MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on query_frontier? +

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

What risk level is query_frontier? +

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

Can I rate-limit query_frontier? +

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

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

query_frontier is provided by the Fillin MCP server (https://fillin.glyphapi.dev/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Fillin tool call.

Deterministic rules across all 11 Fillin tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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