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APonkratov

Yandex Tracker MCP Server

by APonkratov

Add Worklog

issue_add_worklog

Log time spent on a Yandex Tracker issue by specifying issue ID, duration, and optionally a start time and comment. Keep accurate worklogs for better project tracking.

Instructions

Add a worklog entry (log spent time) to a Yandex Tracker issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startNoOptional start datetime for the worklog. If timezone is not provided, UTC is assumed.
commentNoOptional comment to add to the worklog entry.
durationYesTime spent in ISO-8601 duration format (e.g., 'PT1H30M').
issue_idYesIssue ID in the format '<project>-<id>', like 'SOMEPROJECT-1'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
issueNo
startNo
commentNo
durationNoRaw Tracker ISO 8601 duration. Week-based values use five working days per week and must not be converted to calendar weeks.
createdAtNo
createdByNo
updatedAtNo
updatedByNo
Behavior3/5

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

The annotation readOnlyHint=false already signals this is a write operation, and the description's 'Add' aligns. However, the description adds no additional behavioral context such as whether the worklog is appended, any permission requirements, or that it will be visible via issue_get_worklogs. It does not contradict annotations, but also provides no extra transparency beyond the annotation.

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 precisely captures the tool's purpose without unnecessary verbosity. It is front-loaded with the verb and resource, making it easy to scan.

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 simple nature of the operation, rich parameter schema, and presence of an output schema, the description is adequate for a basic add-worklog tool. It clearly indicates the primary action, though it could have mentioned typical side effects or that worklogs are associated with an issue, but those are already implied by the schema and tool name.

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?

Since the schema description coverage is 100%, the parameters are already fully documented in the schema. The tool description itself adds no additional meaning to parameters, instead relying on the schema's definitions for issue_id, duration, start, and comment. This meets the baseline but does not exceed it.

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 ('Add a worklog entry') and the specific resource ('to a Yandex Tracker issue'), with the parenthetical 'log spent time' clarifying intent. It distinguishes from sibling tools like issue_update_worklog and issue_delete_worklog by focusing on the creation aspect.

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 the tool is for logging time on an issue, but provides no explicit guidance on when to use it versus alternatives such as issue_update_worklog or issue_delete_worklog. There are no exclusions or alternative recommendations, leaving usage context implicit.

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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