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batch_complete_tasks

Batch complete up to 50 tasks in a single call, setting each as COMPLETED or FAILED with message, PR URL, and commit hash.

Instructions

Complete multiple AI tasks in a single call. Each entry can have its own message, prUrl, and commitHash. Status defaults to COMPLETED.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYesArray of tasks to complete (max 50)
teamIdNoTeam ID (auto from session if omitted)
projectIdNoProject ID (auto from session if omitted)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It explains the default status and per-entry fields, but does not disclose the effect on tasks, whether completion is reversible, partial failure behavior, authentication needs, or return/error semantics. This is a significant gap for a mutating batch operation.

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 short front-loaded sentences with no filler. The first sentence captures the core operation, and the second adds useful per-entry variation details without redundancy or excess length.

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?

With no annotations and no output schema, this description is too thin for a mutating batch operation. An agent does not know what 'complete' does to the tasks, what the response will be, or how failures in the batch are handled. The schema is thorough, but the description does not complete the operational picture.

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?

Schema description coverage is 100%, so the baseline is 3. The description repeats some parameter information (message, prUrl, commitHash, default status) but adds no meaning beyond what the schema already documents.

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 states a specific verb+resource: 'Complete multiple AI tasks in a single call.' It clearly distinguishes this batch variant from single-task siblings like complete_ai_task and from batch_start_tasks, without requiring schema inspection.

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?

The phrase 'multiple AI tasks in a single call' provides clear usage context: use this when completing several tasks at once. It does not explicitly name an alternative or state when not to use it, but the batch framing is sufficient for basic routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.