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multidimensionalcats

kanban-mcp

add_decision

Record a decision on a kanban item, capturing the choice, rejected alternatives, and rationale for future reference.

Instructions

Add a decision record to an item.

Args: item_id: The item to attach the decision to choice: What was decided (max 200 chars) rejected_alternatives: What was rejected (max 500 chars) rationale: Brief reason for the choice (max 200 chars)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
choiceYeschoice parameter
item_idYesitem_id parameter
rationaleNorationale parameter
rejected_alternativesNorejected_alternatives parameter
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 burden. It states 'Add' which implies mutation, but does not disclose any side effects, permission requirements, or behavior on failure. The max character limits are helpful but not behavioral traits.

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 concise, front-loaded with the primary action, and uses an organized args list. Some redundancy exists with the schema's parameter descriptions, but the added constraints keep it efficient and readable.

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

Completeness3/5

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

The tool is a simple mutation with no output schema and no annotations. The description covers the purpose and parameters adequately for a basic add operation, but it omits details about the return value or success/failure behavior, which leaves some gaps for an AI agent.

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?

While the schema covers all parameters at 100%, the descriptions in the schema are generic ('choice parameter'). The tool description adds real meaning: it explains what each parameter represents (e.g., 'What was decided', 'What was rejected') and provides max length constraints, exceeding the schema's 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 the action ('Add a decision record') and the target ('to an item'), distinguishing it from sibling tools like delete_decision and get_item_decisions. The verb and resource are specific and unambiguous.

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

Usage Guidelines3/5

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

The description does not explicitly mention when to use this tool versus alternatives, but the unique purpose among siblings makes the usage context implied. There is no exclusion or alternative mentioned, so it sits at the 'implied usage' level.

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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