Medium Risk

chieflab_record_manual_publish

USE WHEN the user has manually posted to a channel returned by chieflab_use_manual_fallback (Product Hunt / HN / Reddit / Discord / etc.) and wants to feed the live URL back to ChiefLab so the closed loop continues. Records the URL on the original publishAction (status flips from 'approved' to 'e...

Part of the ChiefLab server.

chieflab_record_manual_publish can modify ChiefLab data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use chieflab_record_manual_publish to create or modify resources in ChiefLab. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call chieflab_record_manual_publish repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach ChiefLab.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "chieflab_record_manual_publish": {
      "limits": [
        {
          "counter": "chieflab_record_manual_publish_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access chieflab_record_manual_publish 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 chieflab_record_manual_publish only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the chieflab_record_manual_publish tool do? +

USE WHEN the user has manually posted to a channel returned by chieflab_use_manual_fallback (Product Hunt / HN / Reddit / Discord / etc.) and wants to feed the live URL back to ChiefLab so the closed loop continues. Records the URL on the original publishAction (status flips from 'approved' to 'executed' with metadata.executedManually=true + metadata.publishedUrl), persists a proof_asset to the P9 company brain, and queues 24-hour metrics readback via chiefmo_post_launch_review. Without this tool, manually-posted channels are lost to ChiefLab's measurement loop.. It is categorised as a Write tool in the ChiefLab MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on chieflab_record_manual_publish? +

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

What risk level is chieflab_record_manual_publish? +

chieflab_record_manual_publish is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit chieflab_record_manual_publish? +

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

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

chieflab_record_manual_publish is provided by the ChiefLab MCP server (@chieflab/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every ChiefLab tool call.

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