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tool_csdn_stats

Fetch view, like, comment, and collect counts for a published CSDN article using its public endpoint, so you can track post performance after publishing.

Instructions

Fetch view/like/comment/collect counts for a published CSDN article.

Uses CSDN's public article-detail JSON endpoint (no login required). Call this after publish_csdn to track how a post is doing.

Args: article_url: Full CSDN article URL (e.g. https://blog.csdn.net//article/details/).

Returns: dict with {ok, article_url, article_id, title, views, likes, comments, collects, publish_time}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
article_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the data source (public article-detail JSON endpoint) and that no login is required, which is exactly the auth/permission context an agent needs. It omits failure behavior (unpublished or deleted article) and any rate-limit caveats, keeping it out of 5 territory.

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?

Front-loaded purpose sentence, a routing instruction, then compact Args/Returns blocks. Every line adds information and nothing is padded or restated.

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?

No output schema exists, so listing the return dict keys (ok, article_url, article_id, title, views, likes, comments, collects, publish_time) is necessary and it is present. Combined with the auth note and URL format, an agent has everything needed to call this 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?

Schema coverage is 0% and the single required param is undocumented in the schema, but the description compensates by specifying the exact expected format with a concrete URL example (https://blog.csdn.net/<user>/article/details/<id>). Repeating the format inline is non-trivial value over the bare string type.

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?

States a specific verb (fetch) and resource (view/like/comment/collect counts) scoped to a published CSDN article, which cleanly distinguishes it from siblings like publish_csdn or list_drafts. No ambiguity about what data comes back.

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

Usage Guidelines4/5

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

"Call this after publish_csdn to track how a post is doing" gives explicit sequencing and intent, so the agent knows when this tool is in play. It stops short of stating exclusions (e.g. that it only works for already-published URLs, not drafts), so a 4 rather than a 5.

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