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summarize_article_for_query

Extract relevant Wikipedia article summaries focused on specific queries to quickly find targeted information within articles.

Instructions

Get a summary of a Wikipedia article tailored to a specific query.

The summary is a snippet around the query within the article text or summary. The max_length parameter controls the length of the snippet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
queryYes
max_lengthNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function for the summarize_article_for_query tool. Decorated with @server.tool() for registration. Calls WikipediaClient.summarize_for_query and formats the response.
    @server.tool()
    def summarize_article_for_query(
        title: str,
        query: str,
        max_length: Annotated[int, Field(title="Max Length")] = 250,
    ) -> Dict[str, Any]:
        """
        Get a summary of a Wikipedia article tailored to a specific query.
    
        The summary is a snippet around the query within the article text or
        summary. The max_length parameter controls the length of the snippet.
        """
        logger.info(f"Tool: Getting query-focused summary for article: {title}, query: {query}")
        summary = wikipedia_client.summarize_for_query(title, query, max_length=max_length)
        return {"title": title, "query": query, "summary": summary}
  • The @server.tool() decorator registers the summarize_article_for_query function as an MCP tool.
    @server.tool()
  • Core helper method in WikipediaClient that implements the query-focused summary by extracting a snippet of article text around occurrences of the query.
    def summarize_for_query(self, title: str, query: str, max_length: int = 250) -> str:
        """
        Get a summary of a Wikipedia article tailored to a specific query.
    
        This is a simplified implementation that returns a snippet around the query.
    
        Args:
            title: The title of the Wikipedia article.
            query: The query to focus the summary on.
            max_length: The maximum length of the summary.
    
        Returns:
            A query-focused summary.
        """
        try:
            page = self.wiki.page(title)
            if not page.exists():
                return f"No Wikipedia article found for '{title}'."
    
            text_content = page.text
            query_lower = query.lower()
            text_lower = text_content.lower()
    
            start_index = text_lower.find(query_lower)
            if start_index == -1:
                # If query not found, return the beginning of the summary or article text
                summary_part = page.summary[:max_length]
                if not summary_part:
                    summary_part = text_content[:max_length]
                return summary_part + "..." if len(summary_part) >= max_length else summary_part
    
            # Try to get context around the query
            context_start = max(0, start_index - (max_length // 2))
            context_end = min(len(text_content), start_index + len(query) + (max_length // 2))
    
            snippet = text_content[context_start:context_end]
    
            if len(snippet) > max_length:
                snippet = snippet[:max_length]
    
            return snippet + "..." if len(snippet) >= max_length or context_end < len(text_content) else snippet
    
        except Exception as e:
            logger.error(f"Error generating query-focused summary for '{title}': {e}")
            return f"Error generating query-focused summary for '{title}': {str(e)}"
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. It explains that the summary is 'a snippet around the query within the article text or summary' and mentions max_length controls snippet length, which adds some behavioral context. However, it lacks critical details like whether this is a read-only operation, potential rate limits, error conditions (e.g., if the query isn't found), or how the snippet is generated (e.g., proximity-based). For a tool with no annotations, this is insufficient.

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

Conciseness4/5

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

The description is appropriately concise with two sentences. The first sentence front-loads the core purpose, and the second adds necessary details about the snippet nature and max_length. There's no wasted text, though it could be slightly more structured (e.g., bullet points for clarity).

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

Completeness3/5

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

Given no annotations, 0% schema description coverage, but an output schema exists (so return values are documented elsewhere), the description is moderately complete. It covers the basic operation and max_length parameter but misses key contextual elements like behavioral traits (e.g., read-only status), parameter semantics for 'title' and 'query', and usage guidelines relative to siblings. It's adequate for a simple tool but has clear gaps.

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?

Schema description coverage is 0%, so the description must compensate. It explains that 'max_length parameter controls the length of the snippet', which adds meaning beyond the schema's type information. However, it doesn't clarify what 'title' and 'query' represent (e.g., article title vs. page ID, query as search term vs. section heading), leaving two of three parameters with minimal semantic context. The description provides some value but doesn't fully address the coverage gap.

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 tool's purpose: 'Get a summary of a Wikipedia article tailored to a specific query.' It specifies the verb ('Get a summary'), resource ('Wikipedia article'), and scope ('tailored to a specific query'), which distinguishes it from generic summary tools like 'get_summary'. However, it doesn't explicitly differentiate from 'summarize_article_section', which is a close sibling.

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. It doesn't mention when this tool is appropriate compared to 'get_summary' (which likely provides a general summary) or 'summarize_article_section' (which focuses on specific sections). There's no context about prerequisites, exclusions, or comparative use cases with siblings like 'search_wikipedia' or 'extract_key_facts'.

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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