Skip to main content
Glama
kajirita2002

honeycomb-mcp-server

honeycomb_slo_create

Create a new Service Level Objective (SLO) for a specific dataset or all datasets, defining objectives, SLIs, and time periods for monitoring and performance tracking.

Instructions

Create a new SLO for a dataset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetSlugYesDataset slug to create SLO for, or 'all' for all datasets
descriptionNoDescription of the SLO
nameYesName of the SLO
objectiveNoObjective configuration with target and time window
sliNoService Level Indicator configuration
time_periodNoTime period configuration for the SLO
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but provides no information about permissions required, whether this is a mutating operation, what happens on success/failure, rate limits, or any side effects. For a tool that creates SLOs (likely requiring specific permissions), this is insufficient.

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 states the core purpose without unnecessary words. It's appropriately sized for a creation tool and gets straight to the point.

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 tool that creates SLOs (likely a mutating operation requiring specific permissions) with no annotations and no output schema, the description is inadequate. It doesn't explain what an SLO is in Honeycomb context, what happens after creation, or provide any behavioral context. The agent would need to infer too much from just the description and schema.

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 description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting, though the description could have provided context about how parameters relate to SLO creation.

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 SLO for a dataset'), making the purpose understandable. However, it doesn't differentiate this tool from its sibling 'honeycomb_slo_update', which would be important for an agent to distinguish between creation and modification operations.

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 like 'honeycomb_slo_update' or 'honeycomb_slos_list'. There's no mention of prerequisites, constraints, or typical use cases for SLO creation in the Honeycomb context.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kajirita2002/honeycomb-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server