Guides you through defining a relationship between two Honeydew entities — covering join type, direction, cross-filtering, and connection method — then pushes the updated entity YAML to Honeydew via the MCP tools.
Scanned 9/12/2026
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npx -y skills add thedixitjain/the-mega-skill-library --skill relation-creation --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: relation-creation
description: "Guides you through defining a relationship between two Honeydew entities — covering join type, direction, cross-filtering, and connection method — then pushes the updated entity YAML to Honeydew via the MCP tools."
category: ai-agents-and-harness
source_repo: hashgraph-online/awesome-codex-plugins
source_path: "plugins/honeydew-ai/honeydew-ai-coding-agents-plugins/skills/relation-creation/SKILL.md"
source_url: https://github.com/hashgraph-online/awesome-codex-plugins/blob/HEAD/plugins/honeydew-ai/honeydew-ai-coding-agents-plugins/skills/relation-creation/SKILL.md
---
## Prerequisites
Before creating relations, ensure you are on the correct workspace and branch. Use `get_session_workspace_and_branch` to check the current session context. For development work, create a branch with `create_workspace_branch` (the session switches automatically). See the `model-exploration` skill for the full workspace/branch tool reference.
---
## Overview
A Honeydew **relation** defines how two entities join together.
Relations are not standalone objects — they live inside the **source entity's YAML** as a `relations:` block.
Every relation connects the "many" side to the "one" side: for example, `orders` (many) → `customers` (one).
Relations enable:
- Metrics on one entity to reference attributes from another
- Cross-entity calculated attributes (Multi-Entity type)
- Filter propagation between entities in BI queries
> Relations are defined on the source entity. To add a relation, use `update_object` on the entity that holds the foreign key (the "many" side).
---
## Creation Methods
### Primary: update_object on the Source Entity
There is no `create_relation` tool. Adding a relation means updating the source entity's YAML to include the `relations:` block.
Call `update_object` with:
- `yaml_text` — the full updated entity YAML with the `relations:` block
- `object_key` — the entity's object key (find via `list_entities` or `get_entity`)
Required permission: Editor or higher.
### After Creation/Update: Display the UI Link
After a successful `update_object` call, the response includes a `ui_url` field. **Always display this URL to the user** so they can quickly open the object in the Honeydew application.
### Remove a Relation: update_object
There is no `delete_object` for relations. To remove a relation, update the source entity's YAML with the relation removed from the `relations:` block.
1. **Find which entity defines the relation.** The relation lives in only one entity's YAML, but it could be on either side. Use `get_entity` on both entities and check which one has the relation in its `relations:` block.
2. Remove the target relation from that entity's `relations:` list (keep all other relations intact).
3. Call `update_object` with the updated YAML and the entity's `object_key`.
---
## Decision Flow
```
Need to define a relation?
│
├─► Simple FK join (equality on one or more columns)?
│ └─► Use field-based connection
│ connection:
│ - src_field: <fk_column>
│ target_field: <pk_column>
│
├─► Complex join (range, filter, SCD Type 2, multi-entity)?
│ └─► Use expression-based connection
│ connection_expr:
│ sql: |-
│ <custom SQL>
│
└─► Removing an existing relation?
└─► Use update_object — remove relation from entity YAML
```
---
## Examples
See [examples.md](examples.md) for full worked examples covering: field-based join, composite key, expression-based (SCD Type 2), multiple relations, and removing a relation.
---
## Discovery Helpers
Use these MCP tools before defining relations:
- `get_entity` — Get entity details including existing relations, attributes, and YAML definition
- `list_entities` — List all entities (to identify source and target)
- `search_model` — Search for entities or fields by name (use `search_mode: EXACT` for known names, `OR` for broad discovery)
---
See [reference.md](reference.md) for: YAML schema, relation direction (rel_type), join types, cross-filtering options, and connection methods.
---
## Pre-Implementation: Present Modeling Options
**IMPORTANT: Before creating any relations, analyze the modeling options and present them to the user for decision.**
Steps:
1. **Examine the existing model** — Review current entities and relations using `list_entities` and `get_entity`
2. **Identify viable approaches** — There are often multiple valid ways to connect entities (e.g., direct connections, through intermediate entities, different join types, cross-filtering choices)
3. **Present trade-offs** — Explain the pros/cons of each approach in context of the user's data and use cases
4. **Get user confirmation** — Ask the user which approach they prefer before implementing
**Do not assume a single correct answer.** Relationship modeling involves trade-offs (query performance, maintainability, analytical flexibility) that depend on the user's specific needs.
---
## Documentation Lookup
Use the `honeydew-docs` MCP tools to search the Honeydew documentation when:
- You need to understand join types, cross-filtering behavior, or relationship modeling patterns in more depth
- The user asks about how relations affect query behavior or metric calculations
- You need guidance on advanced modeling scenarios like SCD Type 2 joins, self-referencing relations, or multi-path joins
- The user asks about relation performance implications or troubleshooting join issues
- The user needs advanced modeling patterns for complex relationship topologies
Search for topics like: "relations", "joins", "cross-filtering", "many-to-one", "relationship modeling".
---
## Best Practices
- **Define relations on the "many" side.** The entity holding the FK is the source; use `rel_type: many-to-one`.
- **Use field-based connections for simple FK joins.** Reserve `connection_expr` for cases that genuinely require custom SQL.
- **Include all key columns in field-based connections.** If the "one" side has a composite key, all parts must be listed in `connection`.
- **Default to `cross_filtering: both`** unless performance is a concern. Restrict to `one-to-many` or `none` for large entities.
- **Always include existing relations when using update_object.** Updating an entity's YAML replaces the full `relations:` block — omitting an existing relation will delete it.
- **Use get_entity before modifying.** Always inspect current entity YAML and relations before updating to avoid accidentally removing existing ones.
- **Minimize YAML changes.** Preserve the existing field order and formatting. Only change what you need to. Objects are versioned in git, so unnecessary reordering or reformatting creates noisy diffs.
---
## MANDATORY: Validate After Creating
**After creating ANY relation, you MUST invoke the `validation` skill to test and validate.**
See the `validation` skill (Entities → "Validating Relations") for:
- How to verify relation exists via `get_entity`
- How to test cross-entity queries work
- Sanity checks (join works, no fan-out, NULLs reasonable)
- When to alert the user about issues
**Quick validation:**
1. Verify relation exists using `get_entity` on the source entity, check its relations list.
2. Test cross-entity query using `get_data_from_fields`:
- `attributes`: `["<target_entity>.<attribute>"]`
- `metrics`: `["<source_entity>.<metric>"]`
---
## Common Pitfalls to Avoid
- **Replacing existing relations unintentionally.** `update_object` replaces the full entity YAML. If the entity already has relations, fetch the current YAML first (via `get_entity`) and include all of them in the update.
- **Defining relation on the wrong entity.** Relations should be defined on the entity that holds the FK (the "many" side). Defining on the "one" side inverts the semantics.
- **Missing key columns in field-based connections.** If the target entity has a composite key, all columns must appear in `connection`. A partial key join produces fan-out and incorrect aggregations.
- **Using `connection_expr` without enforcing cardinality.** Custom SQL joins bypass Honeydew's cardinality validation. A poorly written expression can silently produce many-to-many joins.
- **`many-to-one` cross-filtering on large tables.** Filtering from the "many" side back to the "one" side requires a reverse join and is expensive. Use `none` or `one-to-many` unless the use case requires it.
---
**Source:** [`hashgraph-online/awesome-codex-plugins`](https://github.com/hashgraph-online/awesome-codex-plugins) → `plugins/honeydew-ai/honeydew-ai-coding-agents-plugins/skills/relation-creation/SKILL.md`
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