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ya-tracker-mcp

ya-tracker-mcp

by imdeniil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

find_assignee

Identify a team member for an issue by area expertise (e.g., 'API') or queue key (e.g., 'DEV') to assign the right person.

Instructions

Find a team member by area of expertise or queue.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "find_assignee"
  }
}

Input Schema

NameRequiredDescriptionDefault
areaNoArea keyword (e.g. "API", "React", "testing")
queueNoQueue key (e.g. "DEV")
output_formatNoResponse format: "text" (default, markdown) or "json"text

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.2

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It only states the basic function without mentioning return cardinality (single vs. list), matching semantics, or read-only safety. This adds little beyond the name.

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 sentence of 10 words, concise and front-loaded with the primary action, making it highly efficient.

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?

Given the output schema exists (per context), return values are covered. The tool is simple with optional parameters well-documented in the schema. The description is minimal but adequate for basic use, though it could clarify whether results are singular or multiple.

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?

Schema coverage is 100% with descriptive parameter definitions (e.g., area keyword examples). The description adds minimal meaning by linking area to expertise and queue, but this is already implied by the schema, so it does not significantly elevate understanding beyond baseline.

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 specific action (Find) and resource (team member), and adds search criteria (area of expertise or queue), distinguishing it from siblings like list_team or get_team_member.

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?

The description implies usage for finding a team member by expertise or queue, but provides no explicit guidance on when to use this versus alternatives like list_team or get_team_member, nor any exclusions or prerequisites.

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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