retry_app_release_stage_pipeline

[application delivery] 重试变更请求的发布流程阶段流水线

SERVERAlibabacloud Devops SOURCEalibabacloud-devops-mcp-server

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/alibabacloud-devops/retry-app-release-stage-pipeline.md

WHAT IT DOES

What retry_app_release_stage_pipeline does on Alibabacloud Devops

AI agents invoke retry_app_release_stage_pipeline to trigger actions in Alibabacloud Devops. 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.

RISK

Why retry_app_release_stage_pipeline is rated High

Retrying a release stage pipeline re-triggers an external execution process (CI/CD pipeline) that can deploy code to environments. This is an Execute action with high severity because misuse could deploy unintended changes to production systems.

From the tool's definition 'retry' + '发布流程阶段流水线' (retry the release pipeline stage of a change request) — triggers re-execution of a deployment pipeline

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs retry_app_release_stage_pipeline safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Alibabacloud Devops, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For retry_app_release_stage_pipeline, this is the rule to start with:

retry_app_release_stage_pipeline Rate-limited

retry_app_release_stage_pipeline 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "retry_app_release_stage_pipeline": {
      "limits": [
        {
          "counter": "retry_app_release_stage_pipeline_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Alibabacloud Devops, apply this rule, and every retry_app_release_stage_pipeline call is checked against it from then on.

FAQ

Questions about retry_app_release_stage_pipeline

What does the retry_app_release_stage_pipeline tool do? +

[application delivery] 重试变更请求的发布流程阶段流水线. It is categorised as a Execute tool in the Alibabacloud Devops MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on retry_app_release_stage_pipeline? +

Register the Alibabacloud Devops MCP server in PolicyLayer and add a rule for retry_app_release_stage_pipeline: 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 Alibabacloud Devops. Nothing to install.

What risk level is retry_app_release_stage_pipeline? +

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

Can I rate-limit retry_app_release_stage_pipeline? +

Yes. Add a rate_limit block to the retry_app_release_stage_pipeline 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.

How do I block retry_app_release_stage_pipeline completely? +

Set action: deny in the PolicyLayer policy for retry_app_release_stage_pipeline. 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 retry_app_release_stage_pipeline? +

retry_app_release_stage_pipeline is provided by the Alibabacloud Devops MCP server (alibabacloud-devops-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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