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Obsidian MCP Extended

Obsidian MCP Extended

by aleksakarac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_kanban_statistics_tool

Get comprehensive Kanban board statistics: total, completed, and incomplete card counts, per-column completion rates, and overall progress percentage.

Instructions

Get comprehensive statistics for a Kanban board (filesystem-native, offline).

Analyzes the board and provides:

  • Total cards, completed, incomplete counts

  • Per-column card counts and completion rates

  • Overall board completion percentage

  • Column names and structure

When to use:

  • Project progress tracking

  • Sprint velocity analysis

  • Board health monitoring

  • Generating board reports

Performance:

  • Boards with 100 cards: < 500ms

  • Boards with 1,000 cards: < 5 seconds

Returns: Comprehensive board statistics with counts and percentages

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": {
      "file_path": "<file_path>"
    },
    "name": "get_kanban_statistics_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYesPath to Kanban board file (relative to vault)
vault_pathNoPath to vault (optional, uses OBSIDIAN_VAULT_PATH env if not provided)
ctxNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool is offline and gives performance estimates (<500ms for 100 cards, <5s for 1000 cards). However, it does not state that the tool is read-only, discuss permissions, or describe error conditions or edge cases.

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 well-structured with bullet points, sections, and front-loaded purpose. It is reasonably concise at about 10 lines, though the 'Returns:' line is somewhat redundant with the earlier list. Overall efficient and easy to scan.

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 description covers the main use cases and return values, and with no output schema, it provides enough detail on what is returned. However, it lacks information on error handling (e.g., missing file, empty board), and the ctx parameter is undocumented. These gaps reduce completeness for a tool with moderate complexity.

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?

The input schema has 67% description coverage (file_path and vault_path have descriptions, ctx does not). The description adds no parameter-specific information beyond what the schema provides. Without further elaboration on parameter formats or constraints, it meets the baseline for a 3 but does not compensate for the uncovered parameter.

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 gets comprehensive statistics for a Kanban board, specifying 'filesystem-native, offline'. It details what statistics are provided (total cards, per-column counts, completion rates) and distinguishes itself from related sibling tools like parse_kanban_board_tool and note_statistics_fs_tool.

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 includes an explicit 'When to use' section listing four scenarios: project progress tracking, sprint velocity analysis, board health monitoring, and generating board reports. This provides clear context for usage, though it does not explicitly mention when not to use the tool or suggest alternatives.

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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