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list_wiki_pages

Retrieve all wiki pages from an Azure DevOps project to view documentation content and structure.

Instructions

Lists all pages in a wiki.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesThe name or ID of the project.
wiki_identifierYesThe name or ID of the wiki.

Implementation Reference

  • Core handler function that implements the list_wiki_pages tool logic by calling the Azure DevOps WikiClient to batch fetch wiki pages and formatting the response.
    def list_wiki_pages(self, project, wiki_identifier):
        pages_batch_request = WikiPagesBatchRequest(
            top=100  # Retrieve up to 100 pages
        )
        pages = self.wiki_client.get_pages_batch(
            project=project,
            wiki_identifier=wiki_identifier,
            pages_batch_request=pages_batch_request
        )
        return [
            {
                "path": page.path,
                "url": getattr(page, 'url', ''),  # Handle missing url attribute
                "view_stats": [
                    {"date": stat.date.isoformat(), "count": stat.count}
                    for stat in page.view_stats
                ] if page.view_stats else []
            }
            for page in pages
        ]
  • Input schema definition for the list_wiki_pages tool, specifying required parameters project and wiki_identifier.
    types.Tool(
        name="list_wiki_pages",
        description="Lists all pages in a wiki.",
        inputSchema={
            "type": "object",
            "properties": {
                "project": {
                    "type": "string", 
                    "description": "The name or ID of the project."
                },
                "wiki_identifier": {
                    "type": "string", 
                    "description": "The name or ID of the wiki."
                },
            },
            "required": ["project", "wiki_identifier"],
            "additionalProperties": False
        }
    ),
  • Tool dispatch/registration in the MCP server's _execute_tool method, which handles the tool call by invoking the client method.
    elif name == "list_wiki_pages":
        return self.client.list_wiki_pages(**arguments)
  • Tool registration in the server's tools list, including name, description, and schema for MCP protocol compliance.
    types.Tool(
        name="list_wiki_pages",
        description="Lists all pages in a wiki.",
        inputSchema={
            "type": "object",
            "properties": {
                "project": {
                    "type": "string", 
                    "description": "The name or ID of the project."
                },
                "wiki_identifier": {
                    "type": "string", 
                    "description": "The name or ID of the wiki."
                },
            },
            "required": ["project", "wiki_identifier"],
            "additionalProperties": False
        }
    ),
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Lists' implies a read-only operation, it doesn't specify critical details like pagination behavior, rate limits, authentication requirements, or what 'all pages' entails (e.g., includes archived pages?). This leaves significant gaps for a tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core functionality ('Lists all pages in a wiki'). There is no wasted verbiage or redundant information, making it easy to parse and understand immediately.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., list format, fields included) or address behavioral aspects like error conditions or performance considerations. For a tool with no structured metadata, this minimal description leaves too many unknowns for reliable agent use.

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

Parameters3/5

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

The input schema has 100% description coverage, with clear documentation for both required parameters ('project' and 'wiki_identifier'). The description adds no additional parameter information beyond what's in the schema, so it meets the baseline score of 3 for high schema coverage without compensating value.

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

Purpose4/5

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

The description clearly states the action ('Lists') and resource ('all pages in a wiki'), making the purpose immediately understandable. However, it doesn't distinguish this tool from similar sibling tools like 'get_wiki_page_tree' or 'search_wiki_pages', which also retrieve wiki page information but with different scopes or filters.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'search_wiki_pages' (for filtered searches) and 'get_wiki_page_tree' (for hierarchical views), the agent is left to infer usage based on the name alone, which is insufficient for optimal tool selection.

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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