Low Risk

request_note_publication

Request librarian review for public publication. Source remains private by default. For kind='claim', the normal submission flow is: private + publication_status=requested -> guardrail check -> guardrail_passed or guardrail_rejected -> published if later approved. Use claim_contribution_status(pa...

Risk signalsAccepts file system path (path)

Part of the OpenAkashic server.

request_note_publication 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 request_note_publication to retrieve information from OpenAkashic 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 request_note_publication 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": {
    "request_note_publication": {}
  }
}

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These attack patterns abuse exactly the kind of access request_note_publication 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 request_note_publication 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 request_note_publication tool do? +

Request librarian review for public publication. Source remains private by default. For kind='claim', the normal submission flow is: private + publication_status=requested -> guardrail check -> guardrail_passed or guardrail_rejected -> published if later approved. Use claim_contribution_status(path=...) to inspect that state. Formerly known as check_contribution_status. If you see tool-not-found errors, use claim_contribution_status instead. Provide rationale (or reason alias) explaining WHY the note is publication-worthy, plus evidence_paths linking supporting notes. Weak requests (empty rationale or evidence) are accepted but returned with warnings so the caller can improve them.. It is categorised as a Read tool in the OpenAkashic MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on request_note_publication? +

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

What risk level is request_note_publication? +

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

Can I rate-limit request_note_publication? +

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

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

request_note_publication is provided by the OpenAkashic MCP server (https://knowledge.openakashic.com/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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