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ya-tracker-mcp

ya-tracker-mcp

by imdeniil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_from_preset

Create a Yandex Tracker issue from a preset template. Provide queue, template placeholders, and optional overrides or extra fields to generate the issue.

Instructions

Create an issue from a preset template.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "preset_name": "<preset_name>",
      "queue": "<queue>",
      "input_values": "<input_values>"
    },
    "name": "create_from_preset"
  }
}

Input Schema

NameRequiredDescriptionDefault
queueYesQueue key (e.g. "DEV")
overridesNoOptional dict to override preset params (e.g. {"priority": "normal"})
preset_nameYesPreset key (from list_presets)
extra_fieldsNoAdditional/custom/local fields as dict
input_valuesYesDict of template placeholders (e.g. {"description": "...", "steps": "..."})

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.2

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'Create an issue from a preset template.' It does not mention required permissions, whether overrides are validated, side effects, or the return value. This is minimal and insufficient for a mutation tool.

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, concise sentence with no unnecessary words. It is front-loaded and achieves high efficiency, making every word earn its place.

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

Completeness2/5

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

Given the tool's complexity (5 params, nested objects, output schema) and lack of annotations, the description is too sparse. It fails to explain what a preset template is, how to choose one, or how this tool relates to create_issue, leaving significant gaps for an agent to use it correctly.

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?

The schema provides 100% coverage of all parameters, so the baseline is 3. The description adds no additional meaning about the parameters, such as the relationship between input_values and template placeholders, but the schema descriptions already handle parameter semantics well.

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 action (create), the resource (an issue), and the method (from a preset template), which distinguishes it from the sibling create_issue tool that creates an issue directly. This is a specific verb+resource phrasing with explicit differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives like create_issue, how to obtain preset names, or any prerequisites. It simply states what it does without offering usage context or exclusions.

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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