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V2-Digital

V2.ai Insights Scraper MCP

by V2-Digital

get_post_content

Extract complete blog post content from V2.ai Insights by specifying the post index for analysis and summarization.

Instructions

Returns the full content of the blog post at the specified index

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes

Implementation Reference

  • The core logic for fetching a post's content by its index.
    def _get_post_content(index: int):
        """Returns the full content of the blog post at the specified index"""
        posts = fetch_blog_posts()
        if 0 <= index < len(posts):
            return posts[index]
        else:
            return {"error": f"Invalid index. Available posts: 0 to {len(posts) - 1}"}
  • The MCP tool registration for 'get_post_content'.
    @mcp.tool()
    def get_post_content(index: int):
        """Returns the full content of the blog post at the specified index"""
        return _get_post_content(index)
Behavior2/5

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 states the tool returns content, implying a read-only operation, but does not cover aspects like error handling (e.g., invalid index), performance, or output format. This is a significant gap for a tool with zero 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 with zero waste. It is front-loaded with the core purpose and includes necessary details without redundancy, making it appropriately sized and easy to parse.

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 tool has no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on return values, error cases, and behavioral traits, which are crucial for a read operation. The description does not adequately compensate for the missing structured data.

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 schema description coverage is 0%, so the description must compensate. It adds meaning by specifying that 'index' refers to a blog post index, which is useful beyond the schema's basic type. However, it does not explain index range, format, or examples, leaving some ambiguity, so it partially compensates but not fully.

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 ('Returns') and resource ('full content of the blog post'), specifying what the tool does. However, it does not explicitly differentiate from siblings like 'get_contentful_posts' or 'get_latest_posts', which may also retrieve post content, so it lacks sibling distinction for a perfect score.

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 like 'search_blogs' or 'summarize_post'. It mentions 'at the specified index', which implies usage for a known post index, but does not clarify context, exclusions, or prerequisites, leaving the agent without explicit usage instructions.

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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