Approve or reject the proposed spec/plan. Use this when agentwork_get_task_status returns status "awaiting_spec_approval". Args: task_id: The task ID. approved: True to approve, False to reject. api_key: Your Agentwork API key. rejection_reason: If rejecting, explain what changes you want. Return...
Risk signalsHandles credentials or secrets (api_key)
Part of the Agentwork server.
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AI agents use agentwork_approve_spec to create or modify resources in Agentwork. 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 agentwork_approve_spec 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 Agentwork.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"agentwork_approve_spec": {
"limits": [
{
"counter": "agentwork_approve_spec_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Agentwork policy for all 9 tools.
These attack patterns abuse exactly the kind of access agentwork_approve_spec 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.
Approve or reject the proposed spec/plan. Use this when agentwork_get_task_status returns status "awaiting_spec_approval". Args: task_id: The task ID. approved: True to approve, False to reject. api_key: Your Agentwork API key. rejection_reason: If rejecting, explain what changes you want. Returns: JSON with success and new status.. It is categorised as a Write tool in the Agentwork MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Agentwork MCP server in PolicyLayer and add a rule for agentwork_approve_spec: 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 Agentwork. Nothing to install.
agentwork_approve_spec 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 agentwork_approve_spec 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 agentwork_approve_spec. 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.
agentwork_approve_spec is provided by the Agentwork MCP server (agentwork-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 9 Agentwork tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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