Bind Every AI Agent Tool Call to a Capability Budget

“Agentic” means more than producing a plan. Once an agent can call a terminal, browser, filesystem, or API, that plan becomes a security boundary.

I would require a capability budget for every task:

{
  "task_id": "dep-update-42",
  "expires_at": "2026-07-21T12:00:00Z",
  "filesystem": { "read": ["src/**"], "write": ["package-lock.json"] },
  "commands": ["npm test", "npm audit --json"],
  "network": ["registry.npmjs.org:443"],
  "requires_approval": ["git push", "deploy"]
}

The executor—not the model—must validate each proposed call. A revised plan does not inherit broader authority automatically. It either stays within budget or pauses for a new human decision. Log denials with redacted arguments and the exact policy version so incident responders can distinguish hostile behavior from a stale task definition.

Test four paths:

Attempt	Expected result
Read src/app.ts	allow and log
Write package-lock.json	allow and preserve diff
Read .env	deny before execution
Run an unlisted shell command	deny and require review

The MCP tools specification explicitly recommends human confirmation and visibility around tool invocations. A product still needs an enforceable authorization layer beneath that UX.

I would use this gate when evaluating MonkeyCode: inspect the open-source deployment or run a disposable task on its currently free-to-start cloud platform, then record what authority can be constrained and what remains unknown. Availability and limits can change; free access is not a security control.

I am a MonkeyCode user, not affiliated with the project. This account shares an operator with the other accounts in this publication batch.