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mcp-taskflow

mcp-taskflow

by CalebGerman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

plan_task

Plan and structure tasks by converting natural language descriptions into actionable proposals with goals and expected outcomes.

Instructions

Plan tasks and construct a structured task list. Converts natural language descriptions into actionable task proposals with goals and expected outcomes.

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": {
      "description": "<description>"
    },
    "name": "plan_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
descriptionYes
requirementsNo
existingTasksReferenceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.7/5.0
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 does not say whether planning persists or mutates state, whether it is safe to re-run, what happens to existing tasks, or what the agent gets back — the existingTasksReference parameter hints at state interaction but the description never addresses it.

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

Conciseness4/5

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

Two tight sentences with no filler, front-loading the core action before the elaboration. Efficient, though the second sentence is somewhat redundant with the first rather than adding new operational detail.

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?

For a 3-parameter tool with no annotations, no output schema, and zero schema description coverage, the description is too thin. It should at minimum explain the parameters, whether the result is persisted, and how it relates to the execute/verify lifecycle.

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 description coverage is 0% across 3 parameters. The phrase 'natural language descriptions' loosely maps to the required 'description' field, but 'requirements' and 'existingTasksReference' are undocumented in both schema and description, leaving a real gap the description should have closed.

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?

States a specific verb+resource ('Plan tasks and construct a structured task list') and elaborates with the transformation it performs ('converts natural language descriptions into actionable task proposals with goals and expected outcomes'). The purpose is clear, but it never distinguishes itself from adjacent siblings like split_tasks or analyze_task, so an agent gets no help disambiguating within this crowded family.

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?

No when-to-use, prerequisites, or alternatives are given. With 15 sibling tools including split_tasks, analyze_task, and reflect_task, the absence of routing guidance leaves the agent to guess which planning-stage tool applies.

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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