taskdog-mcp

optimize_schedule

Generate optimal task schedules by applying algorithms to balance priorities, deadlines, and dependencies while respecting maximum daily work hours.

Instructions

Auto-generate optimal task schedules.

Schedules tasks with estimated_duration based on priority, deadlines, and dependencies. By default schedules on weekdays only and skips tasks that already have a planned_start (use force_override to override).

Args: algorithm: Algorithm name. One of: greedy (front-load), balanced (even distribution), backward (JIT from deadline), priority_first (priority only), earliest_deadline (EDF), round_robin (parallel progress), dependency_aware (CPM), genetic (evolutionary), monte_carlo (random sampling). Use list_algorithms() to discover available algorithms. max_hours_per_day: Maximum work hours per day (e.g., 6.0 or 8.0) start_date: Optimization start date in ISO format (e.g., '2025-12-15' or '2025-12-15T09:00:00'). Defaults to server current time when omitted. task_ids: Specific task IDs to optimize. If omitted, all schedulable tasks are considered. force_override: If True, override existing schedules include_all_days: If True, schedule on weekends and holidays too

Returns: Optimization result with successful_tasks, failed_tasks, daily_allocations, and summary metrics.

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": {
      "algorithm": "<algorithm>",
      "max_hours_per_day": "<max_hours_per_day>"
    },
    "name": "optimize_schedule"
  }
}

Input Schema

Name	Required	Description	Default
`task_ids`	No
`algorithm`	Yes
`start_date`	No
`force_override`	No
`include_all_days`	No
`max_hours_per_day`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.26.0Aug 12, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description fully discloses default behavior, override logic, and return values. It even characterizes each algorithm (e.g., 'greedy (front-load)') and notes the start_date default to server time. This is comprehensive behavioral disclosure.

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 well-structured with a clear purpose statement, followed by behavior explanations and Args/Returns sections. Every sentence adds value, and the long algorithm list is necessary for correct tool use.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, 9 algorithms, no schema descriptions or annotations), the description covers all necessary aspects: parameters, defaults, edge cases, and output structure. It also directs users to list_algorithms() for further discovery, completing the contextual picture.

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

Parameters5/5

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

Schema description coverage is 0%, so the description compensates fully by explaining every parameter in Args, including examples, formats, and defaults. The algorithm parameter lists all accepted values with brief semantic descriptions, far exceeding schema capabilities.

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 opening line 'Auto-generate optimal task schedules' clearly states the verb and resource. The description goes on to detail scheduling behavior, algorithm options, and exceptions, making it distinct from sibling task CRUD tools.

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 description explains defaults ('weekdays only', 'skips tasks that already have a planned_start') and conditional parameter usage (force_override, include_all_days). It references list_algorithms() for discovery but does not explicitly compare with alternative scheduling approaches or tools.

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