# Honeyhive

HoneyHive is a modern AI observability and evaluation platform that enables developers and domain experts to collaboratively build reliable AI applications faster.

- **Category:** artificial intelligence
- **Auth:** API_KEY
- **Tools:** 24
- **Triggers:** 0
- **Slug:** `HONEYHIVE`
- **Version:** 20260211_00

## Tools

### Add datapoints to dataset

**Slug:** `HONEYHIVE_ADD_DATAPOINTS_TO_DATASET`

Tool to add datapoints to a dataset. Use when you need to append multiple entries with specified input, ground truth, and history mappings.

### Create Batch Model Events

**Slug:** `HONEYHIVE_CREATE_BATCH_MODEL_EVENTS`

Tool to create multiple model events in a single request. Use when you need to log a batch of event interactions to HoneyHive.

### Create Batch Tool Events

**Slug:** `HONEYHIVE_CREATE_BATCH_TOOL_EVENTS`

Tool to log a batch of external API calls as tool events. Use when you need to record multiple tool events in one request—use after gathering all event data.

### Create Dataset

**Slug:** `HONEYHIVE_CREATE_DATASET`

Tool to create a dataset. Use when you need to initialize a new dataset within a project.

### Create Tool

**Slug:** `HONEYHIVE_CREATE_TOOL`

Creates a new tool definition in a HoneyHive project. Use this to register functions or plugins that can be invoked and tracked within HoneyHive. Tools are defined with a JSON Schema for their parameters, allowing HoneyHive to validate inputs and track tool usage in your AI workflows. Tool names must be unique within a project.

### Delete Datapoint

**Slug:** `HONEYHIVE_DELETE_DATAPOINT`

Tool to delete a specific datapoint by its ID. Use when you need to remove a datapoint from HoneyHive after confirming its identifier.

### Delete Dataset

**Slug:** `HONEYHIVE_DELETE_DATASET`

Tool to delete a dataset by ID. Use when you need to remove a dataset after confirming its ID.

### End Evaluation Run

**Slug:** `HONEYHIVE_END_EVALUATION_RUN`

Tool to update an evaluation run's status and metadata. Use to mark a run as completed after finishing evaluations, or update run properties like name, metadata, configuration, and associated event/datapoint IDs.

### Get Configurations

**Slug:** `HONEYHIVE_GET_CONFIGURATIONS`

Tool to retrieve a list of configurations. Use when you need to fetch all configurations for a specific project before making changes.

### Get Datasets

**Slug:** `HONEYHIVE_GET_DATASETS`

Retrieve datasets from HoneyHive for a specified project. Use this tool when you need to: - List all datasets within a project - Find datasets by type (evaluation or fine-tuning) - Retrieve a specific dataset by its ID Returns dataset details including name, description, datapoints count, type, and timestamps.

### Get Metrics

**Slug:** `HONEYHIVE_GET_METRICS`

Retrieves all metrics associated with a HoneyHive project. Returns a list of metrics including their configuration (name, type, description, thresholds, evaluator details) and metadata (creation/update timestamps, sampling settings). Use this tool when you need to: - List all metrics configured for a project - Get metric IDs for updating metrics via HONEYHIVE_UPDATE_METRIC - Understand what evaluations are set up for a project Prerequisites: Obtain a valid project_name using HONEYHIVE_GET_PROJECTS first.

### Get Projects

**Slug:** `HONEYHIVE_GET_PROJECTS`

Tool to retrieve all projects in the HoneyHive account. Use when you need to list available projects, get project IDs for use in other API calls, or search for a specific project by name.

### List Tools

**Slug:** `HONEYHIVE_LIST_TOOLS`

Tool to list all available Honeyhive tools. Use when you need to discover which functions or plugins are registered for use.

### Retrieve Datapoint

**Slug:** `HONEYHIVE_RETRIEVE_DATAPOINT`

Retrieve a specific datapoint by its ID from HoneyHive. Use this tool when you need the full details of a single datapoint, including its inputs, ground truth, conversation history, linked datasets, and metadata. Prerequisites: You need a valid datapoint ID. Get datapoint IDs from: - HONEYHIVE_RETRIEVE_DATAPOINTS (list datapoints by project/dataset) - HONEYHIVE_ADD_DATAPOINTS_TO_DATASET (returns IDs of newly created datapoints)

### Retrieve Datapoints

**Slug:** `HONEYHIVE_RETRIEVE_DATAPOINTS`

Retrieve datapoints from a HoneyHive project. Use this tool to fetch evaluation datapoints containing inputs, ground truth, and metadata. Supports filtering by specific datapoint IDs or dataset name. Commonly used to: - Review existing test cases before running evaluations - Export datapoints for analysis - Verify datapoint contents after adding them to a dataset

### Retrieve Events

**Slug:** `HONEYHIVE_RETRIEVE_EVENTS`

Retrieve and export events from a HoneyHive project. Use this tool to query traced events (model calls, tool calls, sessions, chains) with optional filters by event_type, metadata, feedback scores, or date range. Returns events with their inputs, outputs, duration, and metrics. Supports pagination for large result sets (max 7500 per page).

### Retrieve Experiment Result

**Slug:** `HONEYHIVE_RETRIEVE_EXPERIMENT_RESULT`

Tool to retrieve the result of a specific experiment run. Use when you need the status, metrics, and datapoint-level details of a completed experiment.

### Start Evaluation Run

**Slug:** `HONEYHIVE_START_EVALUATION_RUN`

Creates a new evaluation run to group and track multiple session events for analysis. Use this action when you want to: - Compare model performance across multiple sessions - Create evaluation batches for quality assurance - Link existing events to datasets for structured evaluation Prerequisites: - Get project ID using Get Projects action - Get event IDs from Start Session or Retrieve Events actions - (Optional) Get dataset ID from Get Datasets action

### Start Session

**Slug:** `HONEYHIVE_START_SESSION`

Start a new HoneyHive session for tracing and observability. Use this tool to initiate a tracking session that groups together related model, tool, and chain events. Returns a session_id that should be used to link subsequent events to this session. Common use cases: - Start tracing a user conversation - Begin logging an LLM pipeline execution - Initialize observability for a batch processing job

### Update Datapoint

**Slug:** `HONEYHIVE_UPDATE_DATAPOINT`

Update an existing datapoint by ID. Use this to modify any combination of inputs, ground_truth, history, metadata, linked_datasets, or linked_evals for a datapoint. Requires a valid datapoint ID obtained from retrieve_datapoints or add_datapoints_to_dataset.

### Update Dataset

**Slug:** `HONEYHIVE_UPDATE_DATASET`

Tool to update an existing dataset. Use when you need to modify a dataset's details (name, description, datapoints, linked evaluations, or metadata) after confirming its ID.

### Update Event

**Slug:** `HONEYHIVE_UPDATE_EVENT`

Update an existing HoneyHive event by ID. Use to attach feedback, metrics, metadata, outputs, config, user properties, or update duration on events created via start_session or batch event creation. At least one optional field must be provided alongside the event_id.

### Update Metric

**Slug:** `HONEYHIVE_UPDATE_METRIC`

Tool to update an existing metric. Use when you need to modify a metric’s properties after creation. Ensure you retrieve the metric first to verify its current state.

### Update Project

**Slug:** `HONEYHIVE_UPDATE_PROJECT`

Updates an existing HoneyHive project's name or description. Use this action to modify project metadata after creation. You must provide the project_id and at least one field to update (name or description). To find project IDs, use the Get Projects action first.
