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PendingSpark

KiraHub MCP Server

by PendingSpark

complete_task

Complete tasks by marking them as done. If validation questions are triggered, answer them by calling again with the message to finalize.

Instructions

Mark a task as completed. This will trigger validation questions based on project knowledge. If validation questions are returned, you must answer them by calling this tool again with the answer in the message parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNoOptional message. Use this to answer validation questions when prompted.
task_idNoID of the task to complete (optional if currently in validation)
Behavior4/5

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

With no annotations, the description carries full burden. It discloses a non-obvious behavior: triggering validation questions based on project knowledge, and instructs the agent to answer them by re-calling the tool. This goes beyond a simple 'complete' and adds useful behavioral context, though it doesn't mention reversibility or permissions.

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 two sentences, front-loaded with the main action, and every sentence provides necessary information. No wasted words.

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?

For a tool with a validation loop, the description covers the flow sufficiently: complete triggers questions, and you answer by re-invoking with the message parameter. It doesn't explicitly state the final outcome after answering all questions, but the behavior is clear enough given the schema and sibling context.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds extra meaning beyond the schema by explaining that 'message' is used to answer validation questions and that 'task_id' is optional during validation. This clarifies when and how to use each parameter, adding value.

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 'Mark a task as completed', a specific verb+resource action. It distinguishes from siblings like update_task by emphasizing the completion and validation trigger. The added validation flow details remove ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context: use to complete a task, and if validation questions are returned, call again with the answer in the message parameter. It doesn't explicitly name alternatives or exclusions, but the process is well-defined.

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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