preset-mcp

create_annotation_layer

Create a new annotation layer that groups time-based annotations for overlaying on time-series charts. Add individual annotations later.

Instructions

Create a new annotation layer.

Annotation layers group time-based annotations that can be overlaid on time-series charts. After creating a layer, use create_annotation to add individual annotations.

Args: name: Name for the annotation layer. descr: Optional description. dry_run: If True, preview the action without executing.

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": {
      "name": "<name>"
    },
    "name": "create_annotation_layer"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`descr`	No
`dry_run`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.2Jun 8, 2026

TDQS

A4.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the 'dry_run' parameter for previewing behavior but does not disclose any destructive implications, auth requirements, or side effects. This is insufficient for a mutation tool.

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 concise, front-loaded with the primary purpose, and includes a structured Args list. Every sentence adds value without redundancy.

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 output schema exists (though not shown), the description adequately covers the creation action. It mentions the dry_run option and links to the next step. Missing details like error handling or response format are minor given the tool's simplicity.

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?

The input schema has no property descriptions (0% coverage), but the tool description adds detailed explanations for all three parameters in the Args block, including purpose and defaults. This greatly compensates 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 'Create a new annotation layer' and explains its purpose: grouping time-based annotations for time-series charts. It distinguishes from the sibling 'create_annotation' by noting that individual annotations are added later.

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 provides a sequential usage hint: 'After creating a layer, use create_annotation to add individual annotations.' This implies when to use this tool. However, it does not explicitly mention prerequisites or when not to use alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server