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ya-tracker-mcp

ya-tracker-mcp

by imdeniil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_trigger_logs

Fetch execution logs for a trigger in a Yandex Tracker queue, with optional issue filtering, to troubleshoot automated workflows.

Instructions

Get trigger execution logs.

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": {
      "queue": "<queue>",
      "trigger_id": "<trigger_id>"
    },
    "name": "get_trigger_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
queueYesQueue key
issue_idNoFilter by issue key
trigger_idYesTrigger ID

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.2

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states 'Get trigger execution logs', mentioning nothing about returned data, ordering, pagination, permissions, rate limits, or any side effects. Given the simplicity of a read operation, the description adds minimal behavioral context.

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 that immediately states the tool's purpose. There is no unnecessary wording or redundancy. It is appropriately sized for a straightforward getter tool, earning a perfect score for efficiency.

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 tool has a simple input schema with 100% parameter coverage and an output schema available, so the description does not need to explain return values. However, the description lacks any context about what 'execution logs' contain, how they are filtered (beyond the parameters), or any limitations. It is minimally viable but leaves some gaps.

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 description coverage is 100%, with each parameter having a clear description ('Queue key', 'Filter by issue key', 'Trigger ID'). The tool description adds no additional semantic value to the parameters, but the baseline of 3 applies because the schema already documents them fully.

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?

The description uses a specific verb ('Get') and a specific resource ('trigger execution logs'), clearly distinguishing it from sibling tools like get_trigger (which retrieves trigger configuration) and get_autoaction_logs (which retrieves logs for autoactions). It doesn't explicitly compare itself to these siblings, but the resource name itself provides sufficient 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, nor any prerequisites or exclusions. It simply states the action, leaving the agent to infer usage from the parameter names and sibling context. No explicit 'when to use' or 'when not to use' is given.

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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