answer_instance_input
Answer a needs_input handoff: an agent paused mid-run because it needs a value it must not invent (work authorization, a notice period, an account detail), and is holding the run open waiting for it. Supply the value and the run continues. The value is saved to the owner
This record as markdown: /tools/io-github-proagentstore-platform/answer-instance-input.md
What answer_instance_input does on ProAgentStore
AI agents invoke answer_instance_input to trigger actions in ProAgentStore. 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 answer_instance_input is rated High
Resumes a live agent execution run by injecting input, triggering continued operations.
From the tool's definition agent paused mid-run...supply the value and the run continues
Attacks that exploit this kind of access
The rule that runs answer_instance_input safely
PolicyLayer is an MCP gateway: it sits between your AI agents and ProAgentStore, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For answer_instance_input, this is the rule to start with:
answer_instance_input 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 ProAgentStore, apply this rule, and every answer_instance_input call is checked against it from then on.
Questions about answer_instance_input
Answer a needs_input handoff: an agent paused mid-run because it needs a value it must not invent (work authorization, a notice period, an account detail), and is holding the run open waiting for it. Supply the value and the run continues. The value is saved to the owner. It is categorised as a Execute tool in the ProAgentStore MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ProAgentStore MCP server in PolicyLayer and add a rule for answer_instance_input: 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 ProAgentStore. Nothing to install.
answer_instance_input 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 answer_instance_input 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 answer_instance_input. 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.
answer_instance_input is provided by the ProAgentStore MCP server (https://mcp.proagentstore.online/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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