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Deepankar1993

Trello MCP Server - Optimized

get_board_lists

Get all lists on a Trello board by providing board ID, showing board structure and list details.

Instructions

Get all lists on a board. Use this tool to see the structure of a board and its lists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoSpecific fields to include in the response. Overrides detailLevel. Use dot notation for nested fields (e.g., 'prefs.permissionLevel')
filterNoFilter lists by status (default: open)
boardIdYesID of the board
maxItemsNoMaximum number of items to return for list operations. Helps reduce response size for large datasets
summarizeNoReturn summary information instead of full data for list operations (e.g., '50 cards' instead of full card array)
detailLevelNoResponse detail level. 'minimal' returns only essential fields, 'standard' returns commonly used fields, 'detailed' returns most fields, 'full' returns all fields (default varies by operation type)
Behavior3/5

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

No annotations are provided, so the description must carry the full transparency burden. It correctly implies a read-only operation, but it states 'Get all lists' while the schema's filter parameter defaults to 'open,' meaning not all lists may be returned. This nuance is not disclosed. The description adds some context ('see the structure') but omits default filter behavior and response shape.

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?

Two short sentences with no wasted words. The information is appropriately front-loaded: the first sentence states the core action, the second provides usage context. Extremely concise and well-structured.

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?

Given the tool's simplicity (no output schema, one required param), the description is adequate. It defines the scope (all lists on a board) and purpose (see structure). It could explicitly mention that it returns lists only, not cards, but the tool name and sibling context make that clear. A minor gap is the lack of reference to get_list for single-list operations, but this does not severely hinder completeness.

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 all six parameters have descriptions. The tool description adds no parameter-specific information beyond what the schema already provides. Baseline 3 is appropriate because the schema carries the full burden.

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 uses a specific verb+resource pattern: 'Get all lists on a board.' It clearly distinguishes from siblings like get_list (singular list) and get_cards_in_list (cards within a list), and the scope is explicit. This fully clarifies what the tool does.

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 second sentence, 'Use this tool to see the structure of a board and its lists,' provides clear usage context. However, it does not explicitly name alternatives or state when not to use it. Still, the context is sufficient for an agent to infer when to call it.

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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