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TAgents

Planning System MCP Server

by TAgents

form_intention

Create a plan to achieve a goal with a hierarchical task tree and inline dependencies. Use draft status for human review before activation, or active for direct execution.

Instructions

Create a plan that achieves a goal, including an initial phase/task tree, in one call. Declare execution order inline: give nodes a ref and list prerequisite refs/titles in depends_on to create 'blocks' edges in the same call — don't ship a bare hierarchy. The response returns a structure summary and warns (created_without_dependencies) when a multi-task plan has no edges. Defaults to status='active' for human-directed creation; pass status='draft' for autonomous loops so a human can review before promotion. Drafts surface in the dashboard pending queue and auto-promote to active when work begins on any node.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goal_idYesGoal this plan serves.
titleYes
descriptionNo
rationaleYesWhy this plan. Surfaces in human review when status=draft.
statusNoactive
visibilityNoprivate
treeNoRecursive tree of nodes (phases, tasks, milestones). Children nest under parents via the 'children' array.
Behavior5/5

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

No annotations exist, so the description fully carries the burden. It explains inline ordering creates 'blocks' edges, response includes structure summary and warnings, and draft auto-promotes when work begins. This is rich behavioral context.

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?

The description is dense and front-loaded with purpose, but could benefit from structuring into bullet points for readability. It is not overly long but is packed with procedural detail.

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?

Covers creation details, dependency definition, status behavior, and response warnings. Missing explicit return value specification (no output schema) and error handling, but sufficient for a creation tool given 7 params.

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 low (43%), but the description adds meaning for key parameters: status (active/draft context), rationale (surfaces in human review), and tree (ref/depends_on usage). It compensates partially for undocumented parameters.

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 the tool creates a plan with a phase/task tree in one call, specifying inline dependency ordering. It distinguishes from siblings like 'extend_intention' by emphasizing one-call creation and edge declaration.

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?

Provides clear guidance on when to use draft vs active status based on loop type, and warns against shipping bare hierarchy. However, it does not explicitly exclude alternatives or mention when not to use this tool.

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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