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open_polarion_login

Launch Polarion login page in browser to authenticate and generate access tokens for requirements management system integration.

Instructions

<purpose>Open Polarion login page in browser for manual authentication</purpose>

<when_to_use>
- When you need to authenticate with Polarion for the first time
- When existing token has expired (401 errors)
- When check_polarion_status() shows no valid token
</when_to_use>

<workflow_position>
STEP 1: Use this tool first if you don't have authentication
STEP 2: Complete login in browser and generate token
STEP 3: Use set_polarion_token() with the generated token
STEP 4: Use check_polarion_status() to verify authentication
STEP 5: Begin exploring with get_polarion_projects()
</workflow_position>

<output>Instructions for manual authentication process</output>

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool handler for open_polarion_login, decorated with @mcp.tool() which also serves as registration. Calls the client helper to open the login page.
    @mcp.tool()
    def open_polarion_login() -> str:
        """
        <purpose>Open Polarion login page in browser for manual authentication</purpose>
        
        <when_to_use>
        - When you need to authenticate with Polarion for the first time
        - When existing token has expired (401 errors)
        - When check_polarion_status() shows no valid token
        </when_to_use>
        
        <workflow_position>
        STEP 1: Use this tool first if you don't have authentication
        STEP 2: Complete login in browser and generate token
        STEP 3: Use set_polarion_token() with the generated token
        STEP 4: Use check_polarion_status() to verify authentication
        STEP 5: Begin exploring with get_polarion_projects()
        </workflow_position>
        
        <output>Instructions for manual authentication process</output>
        """
        logger.info("Opening Polarion login page for manual authentication")
        return polarion_client.open_login_page()
  • Core helper method in PolarionClient that opens the browser to the Polarion login URL and returns JSON instructions for token generation.
    def open_login_page(self) -> str:
        """Open Polarion login page in user's browser for manual authentication"""
        try:
            webbrowser.open(LOGIN_URL)
            
            return json.dumps({
                "status": "success",
                "message": f"Polarion login page opened in your browser: {LOGIN_URL}",
                "instructions": [
                    "1. Complete the login form in your browser",
                    "2. After successful login, navigate to: " + TOKEN_PAGE_URL,
                    "3. Generate a new token manually",
                    "4. Copy the token and use it with the 'set_polarion_token' command"
                ],
                "login_url": LOGIN_URL,
                "token_page_url": TOKEN_PAGE_URL,
                "note": "If you get an 'Internal server error', try refreshing the page or check if the Polarion instance is accessible"
            }, indent=2)
            
        except Exception as e:
            logger.error(f"Failed to open login page: {e}")
            return json.dumps({
                "status": "error",
                "message": f"Failed to open login page: {e}",
                "manual_url": LOGIN_URL
            }, indent=2)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior as opening a browser page for manual authentication, implying it's a read-only initiation step (not destructive) and part of a multi-step process. However, it doesn't specify potential side effects like browser pop-ups or system dependencies, leaving minor gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with labeled sections (<purpose>, <when_to_use>, etc.), making it easy to parse. Each sentence earns its place by providing essential information without redundancy, such as the purpose, usage conditions, workflow steps, and output description, all in a compact format.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (simple browser opener with no parameters), the description is complete. It covers purpose, usage, workflow integration, and output, and with an output schema present, it doesn't need to detail return values. This adequately supports an AI agent in selecting and invoking the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by clarifying that this tool requires no inputs, as it's solely for launching a browser page, which aligns with the empty schema and provides useful context beyond the structured data.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's purpose with a specific verb ('Open') and resource ('Polarion login page'), clearly distinguishing it from sibling tools like 'set_polarion_token' or 'check_polarion_status' by focusing on browser-based manual authentication initiation rather than token management or status checking.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool (e.g., 'for the first time', 'when existing token has expired', 'when check_polarion_status() shows no valid token') and integrates it into a clear workflow with named alternatives (e.g., 'set_polarion_token()', 'check_polarion_status()'), leaving no ambiguity about its role versus siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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