@lodd/mcp-server

create_annotation

Record a user-facing change that may affect analytics, such as after deploying updates to pages or flows, to keep tracking data accurate.

Instructions

Record a user-facing change that may affect analytics. Call after deploying changes to pages, flows, or tracking. Skip dependency updates, CI config, and refactors with no visible impact.

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": {
      "site": "<site>",
      "content": "<content>"
    },
    "name": "create_annotation"
  }
}

Input Schema

Name	Required	Description
`site`	Yes	Site domain or UUID
`content`	Yes	What changed (e.g. 'Simplified checkout to single step')
`timestamp`	No	When it happened (ISO 8601). Defaults to now.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.15Jul 28, 2026

TDQS

A3.8/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states the tool records a change and may affect analytics, but fails to describe side effects, idempotency, rate limits, or what happens on multiple calls. This is minimal for a create operation.

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 two sentences long, with each sentence adding distinct value: first states purpose, second gives usage guidelines. No redundant or filler content.

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?

For a simple creation tool with three well-documented parameters and no output schema, the description is fairly complete. It explains when to use and what to avoid. It could mention the return value, but this is not critical.

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 coverage is 100% (all parameters described), so baseline is 3. The description does not add parameter-specific details beyond the schema; it provides context for the 'content' field but no new meaning.

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 records a user-facing change that may affect analytics, with specific guidance on when to call (after deploying changes to pages, flows, or tracking) and when to skip (dependency updates, CI config, refactors with no visible impact). This distinguishes it from sibling tools like list_annotations and others.

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 explicit when-to-use and when-not-to-use scenarios, giving clear context. However, it does not name alternative tools for other cases, which would strengthen the guidance.

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