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SavageCore

dashy-mcp

dashy_section

Manage dashboard sections in Dashy: add, delete, retrieve, or update section groups and their tiles.

Instructions

dashy section operations on Dashy. Pass operation and an arguments dict matching that operation's parameters.

  • dashy_add_section(section, filename='') — Add a new section (a group of tiles) to the dashboard. section requires a name; common keys: name, icon, items, displayData.

  • dashy_delete_section(sid, filename='') — Delete a section (by index or exact name), including all its items.

  • dashy_get_section(sid, filename='') — Get one section by zero-based index or exact section name.

  • dashy_update_section(sid, patch, filename='') — Shallow-merge patch into a section (by index or exact name). Only the given fields change; a nested array in patch replaces the existing one wholesale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses key behaviors beyond the schema: deletion removes all items, update uses shallow-merge with wholesale replacement of nested arrays, and sections are identified by index or exact name. With no annotations, this level of detail carries the safety and side-effect profile well.

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?

The description is front-loaded with the dispatch pattern and uses a clean bullet list for the four operations. Each line earns its place by adding unique information, with no fluff or repetition. It is appropriately sized for the complexity.

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

Completeness5/5

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

The description covers all operations, parameter nuances, and behavioral edge cases, making it self-contained for selection and invocation. The existence of an output schema means return values need not be described, and none are omitted. It leaves no major gaps for a dispatcher tool of this type.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description is the sole source of parameter meaning. It lists each operation's parameters (e.g., 'section requires a name; common keys: name, icon, items, displayData') and explains the `arguments` dict. This compensates fully for the schema's lack of descriptions.

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 it handles 'dashy section operations' and enumerates four specific sub-operations (add, delete, get, update) with distinct actions. This verb+resource structure distinguishes it from sibling tools like dashy_item and dashy_key.

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?

It explains the dispatch pattern (pass operation and arguments dict) and provides context for each operation, such as 'by index or exact name' and 'shallow-merge patch'. While it doesn't explicitly mention alternatives or when-not-to-use, the scoping to sections is clear.

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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