Low Risk

pathrule_get_context

Return Pathrule context for a workspace path: relevant memories, rules, skills, subtree index, and a next_required_action hint. Remote clients must pass workspace_id; call pathrule_list_workspaces first when unsure. No cwd or local_root_path is used. The response includes a local_runtime.cta line...

Part of the Pathrule server.

pathrule_get_context 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 pathrule_get_context to retrieve information from Pathrule 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 pathrule_get_context 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": {
    "pathrule_get_context": {}
  }
}

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Get this rule live on your own Pathrule 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 pathrule_get_context 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 pathrule_get_context 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 pathrule_get_context tool do? +

Return Pathrule context for a workspace path: relevant memories, rules, skills, subtree index, and a next_required_action hint. Remote clients must pass workspace_id; call pathrule_list_workspaces first when unsure. No cwd or local_root_path is used. The response includes a local_runtime.cta line — surface it when the user could benefit from Pathrule Desktop's hooks, CLAUDE.md/AGENTS.md sync, or on-disk skills.. It is categorised as a Read tool in the Pathrule MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on pathrule_get_context? +

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

What risk level is pathrule_get_context? +

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

Can I rate-limit pathrule_get_context? +

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

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

pathrule_get_context is provided by the Pathrule MCP server (https://mcp.pathrule.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Pathrule tool call.

Deterministic rules across all 30 Pathrule tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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