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log_time

Record hours spent on an issue by specifying the workspace, issue identifier, and hours, with an optional note.

Instructions

Log hours spent on an issue

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": {
      "workspace": "<workspace>",
      "identifier": "<identifier>",
      "hours": "<hours>"
    },
    "name": "log_time"
  }
}

Input Schema

NameRequiredDescriptionDefault
hoursYesHours spent (e.g. 2.5)
workspaceYes
identifierYesIssue id
descriptionNoNote

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.5.1

TDQS

C2.6/5.0
Behavior2/5

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

Annotations supply only destructiveHint=false and a title, so the description carries most of the behavioral burden. "Log hours" does signal a non-destructive write and is consistent with the annotations, but the description says nothing about additivity, duplicate entries, rounding of the hours value, required permissions, or whether the entry is attributed to the caller.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single sentence is front-loaded and free of waste, but it is undersized for a four-parameter mutation tool; there is no structural element such as a required-parameter note or scope clause to earn the space it does not use.

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 a write operation with four parameters, one undocumented parameter, no output schema, and thin annotations, the definition leaves too much for the agent to infer. A caller cannot tell from this alone whether repeated calls stack hours or overwrite, which matters for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%: hours and identifier have descriptions while workspace is undocumented in the schema. The description adds no parameter-level meaning at all — no explanation of what workspace scope means here or how identifier relates to it — so it fails to compensate for the remaining gap.

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?

"Log hours spent on an issue" gives a specific verb (log), a specific resource (hours), and the scope (on an issue), which is enough to distinguish it from read-oriented siblings like list_time_reports. It stops short of explicitly naming a sibling it is not, so it does not reach the top band.

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 contains no when-to-use guidance, no preconditions (issue must exist, workspace membership, whether the issue must be assigned to the caller), and no mention of alternatives such as list_time_reports or finish_work. Usage is only implied by the verb.

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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