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CodexVeritax

stackoverflow-mcp-server

by CodexVeritax

analyze_stack_trace

Analyze programming stack traces to find matching solutions on Stack Overflow. Retrieves relevant questions and answers based on error details, language, and optional filters.

Instructions

Analyze a stack trace and find relevant solutions on Stack Overflow.

Args:
    stack_trace (str): The stack trace to analyze
    language (str): Programming language of the stack trace
    excluded_tags (Optional[List[str]]): Optional list of tags to exclude
    min_score (Optional[int]): Minimum score threshold for questions
    has_accepted_answer (Optional[bool]): Whether questions must have an accepted answer
    answers (Optional[int]): Minimum number of answers
    include_comments (Optional[bool]): Whether to include comments in results
    response_format (Optional[str]): Format of response ("json" or "markdown")
    limit (Optional[int]): Maximum number of results to return
    ctx (Context): The context is passed automatically by the MCP
    
Returns:
    str: Formatted search results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stack_traceYes
languageYes
excluded_tagsNo
min_scoreNo
has_accepted_answerNo
answersNo
include_commentsNo
response_formatNomarkdown
limitNo
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states the high-level purpose and parameter explanations, omitting details such as side effects, permissions, rate limits, or how the stack trace is processed. The absence of such information limits transparency for a tool that likely queries an external API.

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 highly concise and well-structured, with a short introductory sentence followed by a clean bullet-point list of parameters. It front-loads the purpose and uses minimal prose, earning every sentence's place. No extraneous information is present.

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 the tool's complexity (9 parameters) and lack of annotations and output schema, the description adequately explains parameter semantics but fails to describe the return format in sufficient detail ('Formatted search results' is vague). It also does not explain the overall workflow or how results are structured, leaving gaps for an AI agent.

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 description includes an Args section with a one-line explanation for each of the 9 parameters, adding meaning beyond the input schema (which lacks descriptions). All parameters are covered, with clear explanations of their roles (e.g., 'Programming language of the stack trace' for 'language'). However, some explanations are minimal and could benefit from examples or constraints.

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 clearly states the tool's purpose with a specific verb ('analyze') and resource ('stack trace'), and explicitly identifies the target platform (Stack Overflow). It distinguishes itself from sibling tools like 'search_by_error' and 'search_by_query' by focusing on stack trace analysis.

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 does not provide any guidance on when to use this tool versus its siblings (e.g., 'advanced_search', 'search_by_error'). It lacks explicit 'when-to-use' or 'when-not-to-use' instructions, leaving the AI agent without context for choosing the appropriate tool.

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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