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kajirita2002

honeycomb-mcp-server

honeycomb_marker_create

Create markers for datasets to highlight significant events or time ranges, including start/end times, message, type, and optional URL, using the specified dataset slug.

Instructions

Create a new marker for a dataset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetSlugYesDataset slug to create marker for, or 'all' for all datasets
end_timeNoEnd time for the marker (ISO format), optional for point-in-time markers
messageYesMessage for the marker
start_timeYesStart time for the marker (ISO format)
typeYesType of marker
urlNoURL associated with the marker
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention permissions needed, rate limits, whether creation is idempotent, what happens on success/failure, or any side effects, which are critical for a creation 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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

Completeness2/5

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

For a creation tool with no annotations and no output schema, the description is insufficient. It lacks information on behavioral aspects, error handling, and what the tool returns, leaving gaps in understanding how to use it effectively in context.

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 schema description coverage is 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond the schema, such as explaining marker types or usage examples, but meets the baseline since the schema handles parameter details adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('new marker for a dataset'), making the purpose evident. However, it doesn't differentiate from sibling tools like honeycomb_marker_update or honeycomb_marker_delete, which would require mentioning it's specifically for creation rather than modification or deletion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There are no mentions of prerequisites, when-not-to-use scenarios, or comparisons with sibling tools such as honeycomb_marker_update or honeycomb_markers_list, leaving usage context unclear.

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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