update_estimated_effort

[Project Management] 更新已登记的预计工时（云效预计工时受控字段，不能走 update_work_item.customFieldValues）。

SERVERAlibabacloud Devops SOURCEalibabacloud-devops-mcp-server

Medium RISK CLASS

Category Write

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/update-estimated-effort.md

WHAT IT DOES

What update_estimated_effort does on Alibabacloud Devops

AI agents use update_estimated_effort to create or update resources in Alibabacloud Devops, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Alibabacloud Devops environment.

RISK

Why update_estimated_effort is rated Medium

This tool creates or modifies project metadata (estimated effort hours) in a reversible manner. It updates an existing field value rather than executing code or deleting data. The modification is not permanent or irreversible—effort estimates can be corrected or adjusted again.

From the tool's definition Tool name 'update_estimated_effort' and description stating '更新已登记的预计工时' (updates registered estimated effort/hours). The description explicitly indicates this modifies a controlled field in a project management system (云效预计工时受控字段).

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs update_estimated_effort 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 update_estimated_effort, this is the rule to start with:

update_estimated_effort Rate-limited

update_estimated_effort stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_estimated_effort": {
      "limits": [
        {
          "counter": "update_estimated_effort_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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 update_estimated_effort call is checked against it from then on.

FAQ

Questions about update_estimated_effort

What does the update_estimated_effort tool do? +

[Project Management] 更新已登记的预计工时（云效预计工时受控字段，不能走 update_work_item.customFieldValues）。. It is categorised as a Write tool in the Alibabacloud Devops MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_estimated_effort? +

Register the Alibabacloud Devops MCP server in PolicyLayer and add a rule for update_estimated_effort: 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 update_estimated_effort? +

update_estimated_effort is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_estimated_effort? +

Yes. Add a rate_limit block to the update_estimated_effort 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 update_estimated_effort completely? +

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

update_estimated_effort 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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