Mark decisions as consciously overridden for the rest of this session. Phase 3's PreToolUse hook calls this when the agent passes force: true on an Edit tool call to bypass a pre_edit_decision_check block. Adds the surfaced decision IDs to an in-memory session cache; subsequent pre_edit_decision_...
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AI agents use pre_edit_acknowledge to create or modify resources in Kawa Code MCP. 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 pre_edit_acknowledge 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 Kawa Code MCP.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"pre_edit_acknowledge": {
"limits": [
{
"counter": "pre_edit_acknowledge_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Kawa Code MCP policy for all 21 tools.
These attack patterns abuse exactly the kind of access pre_edit_acknowledge gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Mark decisions as consciously overridden for the rest of this session. Phase 3's PreToolUse hook calls this when the agent passes force: true on an Edit tool call to bypass a pre_edit_decision_check block. Adds the surfaced decision IDs to an in-memory session cache; subsequent pre_edit_decision_check fires filter those IDs out so the same block doesn't re-fire. The cache resets when the MCP server process exits (= the agent session ends). For persistent override across sessions, record a fork decision via record_decision(type: "fork", supersedes: [<id>]) instead. Returns: - acknowledged: number of newly-added IDs (existing IDs are deduped silently) - cacheSize: total IDs currently in the session override cache. It is categorised as a Write tool in the Kawa Code MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kawa Code MCP server in PolicyLayer and add a rule for pre_edit_acknowledge: 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 Kawa Code MCP. Nothing to install.
pre_edit_acknowledge is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the pre_edit_acknowledge 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.
Set action: deny in the PolicyLayer policy for pre_edit_acknowledge. 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.
pre_edit_acknowledge is provided by the Kawa Code MCP server (kawacode-ai/kawa.mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 21 Kawa Code MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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