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search_issues

Read-onlyIdempotent

Search YouTrack issues using query syntax with field operators, tags, and relative dates to find issues by project, state, assignee, or text.

Instructions

Search YouTrack issues using query syntax. Use named periods in curly braces for relative dates.

Bare words are a FREE-TEXT match across summaries, descriptions and comments, so a multi-word phrase matches any issue containing any of its words. To scope by field, use operators: project: KEY, State: {In Progress}, Assignee: login, #tag, created: {Last week}, resolved date: 2026-01-01 .. 2026-01-31. Combine them with spaces.

Args: query: YouTrack search query max_results: Max results (default: 50) instance: YouTrack instance (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
instanceNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.21.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds genuine behavioral context beyond that: how bare words are interpreted (free-text across summaries/descriptions/comments) vs field-scoped operators, which is real query-interpretation behavior. It still omits result-count behavior or empty-query handling, so not a 5.

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?

Front-loaded with the core purpose, then progressively denser syntax examples, then the Args section. Every block earns its place for a complex query tool, though the operator examples are dense enough to verge on reference-manual territory.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values needn't be explained, and the description covers params and query semantics thoroughly. Minor gaps remain around pagination/result ordering, but for a search tool this is largely complete.

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%, so the description must carry the parameters, and it does: an Args block documents query, max_results (default 50), and instance (optional), plus rich query-syntax semantics for the primary parameter. The per-arg notes are thin ("YouTrack search query") but the body compensates well for the query parameter.

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?

States a specific verb and resource ("Search YouTrack issues") plus the mechanism (query syntax). It's clear what the tool does, but it never distinguishes itself from close siblings like get_issues, count_issues, or run_saved_search, so an agent can't easily tell which search/list tool applies.

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

Usage Guidelines3/5

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

Usage is only implied: the elaborate query-syntax guidance tells the agent how to use it, but there is no explicit 'use this when...' or exclusion naming alternatives such as get_issues or run_saved_search. The agent must infer the selection condition.

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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