Low Risk

validate_doc_markdown

Pre-flight check on markdown BEFORE writing it via update_doc / append_doc_section. Returns { ok, errors, warnings, parsed } with parsed counts per format type (imageCount, videoCount, mermaidCount, mathCount, svgCount, calloutCount, crossRefCount, mentionCount, embedCount, detailsCount, headingC...

Part of the Dock server.

validate_doc_markdown 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 validate_doc_markdown to retrieve information from Dock 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 validate_doc_markdown 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": {
    "validate_doc_markdown": {}
  }
}

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

Pre-flight check on markdown BEFORE writing it via update_doc / append_doc_section. Returns { ok, errors, warnings, parsed } with parsed counts per format type (imageCount, videoCount, mermaidCount, mathCount, svgCount, calloutCount, crossRefCount, mentionCount, embedCount, detailsCount, headingCount, byteSize, nodeCount, depth) plus structured DocGuardError-equivalent errors (cap breaches) and non-blocking warnings (cross-refs that don't resolve, mention ids that don't resolve, oversize sources, cap-approaching counts). NEVER writes anything; pure parse + analysis. Use when iterating on rich-format markdown to catch problems before burning a write. Cross-ref + mention resolution is gated on caller's accessible workspace set, so unresolved tokens surface in warnings.. It is categorised as a Read tool in the Dock MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on validate_doc_markdown? +

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

What risk level is validate_doc_markdown? +

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

Can I rate-limit validate_doc_markdown? +

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

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

validate_doc_markdown is provided by the Dock MCP server (https://trydock.ai/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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