High Risk →

build_retry_prompt

Given an attempt history, produce the retry feedback message agentcast would append to the conversation when the model returned the wrong shape. Codifies the "validation error as feedback" pattern for non-Node MCP clients.

Part of the Agentcast MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

AI agents invoke build_retry_prompt to trigger processes or run actions in Agentcast. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

build_retry_prompt can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

io-github-mukundakatta-agentcast.yaml
tools:
  build_retry_prompt:
    rules:
      - action: allow
        rate_limit:
          max: 10
          window: 60
        validate:
          required_args: true

See the full Agentcast policy for all 3 tools.

Tool Name build_retry_prompt
Category Execute
Risk Level High

Agents calling execute-class tools like build_retry_prompt have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

build_retry_prompt is one of the high-risk operations in Agentcast. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.

What does the build_retry_prompt tool do? +

Given an attempt history, produce the retry feedback message agentcast would append to the conversation when the model returned the wrong shape. Codifies the "validation error as feedback" pattern for non-Node MCP clients.. It is categorised as a Execute tool in the Agentcast MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on build_retry_prompt? +

Add a rule in your Intercept YAML policy under the tools section for build_retry_prompt. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Agentcast MCP server.

What risk level is build_retry_prompt? +

build_retry_prompt is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit build_retry_prompt? +

Yes. Add a rate_limit block to the build_retry_prompt rule in your Intercept 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.

How do I block build_retry_prompt completely? +

Set action: deny in the Intercept policy for build_retry_prompt. 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.

What MCP server provides build_retry_prompt? +

build_retry_prompt is provided by the Agentcast MCP server (@mukundakatta/agentcast-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Let agents act without letting them run wild.

Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.

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