run_self_directed_delivery_loop
Run a local-first autonomous delivery loop across exploratory research, planning, implementation commands, dogfood, verification, and judge. Persists one durable run in SQLite and emits per-stage receipts so the whole loop can be resumed, audited, and synced later.
This record as markdown: /tools/io-github-homenshum-nodebench/run-self-directed-delivery-loop.md
What run_self_directed_delivery_loop does on Nodebench
AI agents invoke run_self_directed_delivery_loop to trigger actions in Nodebench. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why run_self_directed_delivery_loop is rated High
This tool triggers external operations (exploratory research, implementation commands, dogfood testing, verification) whose effects depend on the loop's internal state and arguments. While it includes persistence and resumability, the core function is executing an autonomous workflow with implementation commands—fitting the Execute category.
From the tool's definition Tool runs an 'autonomous delivery loop' with 'implementation commands' and 'dogfood' (testing/execution), persisting state in SQLite. The description indicates it executes code/commands across exploratory research, planning, and implementation stages.
Attacks that exploit this kind of access
The rule that runs run_self_directed_delivery_loop safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_self_directed_delivery_loop, this is the rule to start with:
run_self_directed_delivery_loop stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every run_self_directed_delivery_loop call is checked against it from then on.
Questions about run_self_directed_delivery_loop
Run a local-first autonomous delivery loop across exploratory research, planning, implementation commands, dogfood, verification, and judge. Persists one durable run in SQLite and emits per-stage receipts so the whole loop can be resumed, audited, and synced later. It is categorised as a Execute tool in the Nodebench MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Nodebench MCP server in PolicyLayer and add a rule for run_self_directed_delivery_loop: 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 Nodebench. Nothing to install.
run_self_directed_delivery_loop is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_self_directed_delivery_loop 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 run_self_directed_delivery_loop. 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.
run_self_directed_delivery_loop is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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