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velesnitski

yt-mcp

by velesnitski

find_comments

Finds issues by matching a phrase or words in comments, with filters for author, project, and max results. Returns newest matches first.

Instructions

Find issues by what their COMMENTS say.

Answers "the ticket where someone wrote …". Two stages: a YouTrack full-text query narrows candidate issues (pass author — a login — to add the commenter: filter), then comments are matched locally: the whole phrase case-insensitively, falling back to all-words when the phrase doesn't appear verbatim. Workflow-bot nags and service stamps are ignored. Newest matches first.

Args: text: Phrase (or words) to find in comment text — required author: Only comments by this login; also narrows the search project: Limit to one project key (optional) max_results: Max matching comments returned (default: 10) instance: YouTrack instance (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
authorNo
projectNo
instanceNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations exist, so description carries full burden. It discloses two-stage process, local matching fallback, ignoring workflow-bot and service stamps, and newest-first ordering. Comprehensive behavioral disclosure.

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?

Description is front-loaded with key info in first sentences and has an organized Args list. Some redundancy (e.g., repeats 'optional') but overall well-structured and concise.

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?

Output schema exists, so return values don't need description. Covers search algorithm, comment filtering, ordering, and all parameters. Complete for a search tool with good context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but description explains all 5 parameters in Args section: text required, author (login narrows search), project (project key), max_results (default 10), instance (optional). Adds meaning beyond schema names and types.

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?

Description states 'Find issues by what their COMMENTS say' and answers the question 'the ticket where someone wrote ...'. Clearly distinguishes from sibling tools like search_issues (which searches other fields) and add_comment (which adds comments).

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?

Explains two-stage search process and fallback behavior but doesn't explicitly state when not to use this tool or compare to alternatives like search_issues. Provides enough context for appropriate use.

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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