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velesnitski

yt-mcp

by velesnitski

add_article_comment

Add a comment to a knowledge base article by providing the article ID and the comment text in markdown.

Instructions

Add a comment to a Knowledge Base article.

Args: article_id: Article ID or database ID text: Comment text (markdown) instance: YouTrack instance (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
instanceNo
article_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

Without annotations, the description must disclose behavioral traits but only mentions that the tool adds a comment. It does not specify if the comment is appended immediately, require user permissions, whether it overwrites existing data, or any rate limits. The optional instance parameter is noted but no behavioral context beyond that.

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 very concise, with only two sentences plus an args list. It is front-loaded with the purpose. However, the args list uses a non-standard docstring format that could be better structured as bullet points or inline sentences for clarity. Still, it avoids unnecessary verbosity.

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?

The description is adequate for a simple create operation, but it lacks contextual completeness. It does not discuss prerequisites (e.g., article existence), error states, or response behavior. Since an output schema exists, return values are not required. However, given the sibling tools and the tool's simplicity, a score of 3 reflects minimal sufficiency.

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 adds meaningful context beyond the input schema's titles. It explains that article_id is 'Article ID or database ID', text is 'Comment text (markdown)', and instance is 'YouTrack instance (optional)'. Given 0% schema coverage, this fully compensates for the schema's lack of description, making the parameters understandable.

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 verb 'Add' and the resource 'comment to a Knowledge Base article', making the tool's purpose unambiguous. It effectively distinguishes itself from sibling tools like 'add_comment' (which targets issue comments) by specifying 'Knowledge Base article'.

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?

No guidance is provided on when to use this tool versus alternatives such as 'add_comment' for issues or 'update_article_comment' for modifications. The description does not include any when-to-use or when-not-to-use directions, leaving the agent to infer from the tool name and resource.

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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