Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add honeydew-ai/honeydew-ai-coding-agents-plugins --skill entity-creationgit clone --depth 1 https://github.com/honeydew-ai/honeydew-ai-coding-agents-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/honeydew-ai/honeydew-ai-coding-agents-plugins/entity-creation)<a href="https://agentmods.dev/skills/honeydew-ai/honeydew-ai-coding-agents-plugins/entity-creation"><img src="https://agentmods.dev/badge/skills/honeydew-ai/honeydew-ai-coding-agents-plugins/entity-creation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/honeydew-ai/honeydew-ai-coding-agents-plugins/entity-creation"><img src="https://agentmods.dev/badge/skills/honeydew-ai/honeydew-ai-coding-agents-plugins/entity-creation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.01860 |
| Opus 5 | $0.00022 | $0.00930 |
| Sonnet 5 | $0.00009 | $0.00372 |
| Haiku 4.5 | $0.00004 | $0.00186 |
Grade A, and why
entity-creation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prerequisites
Before creating entities, 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 workspace-branch skill for the full workspace/branch tool reference.
Overview
A Honeydew entity is the foundational modeling object — a named, governed representation of a business concept at a specific granularity. Every metric and calculated attribute is anchored to an entity. An entity maps to a data warehouse (Snowflake, Databricks, or BigQuery) table, view, custom SQL query, or a virtual derivation from the semantic model.
When creating an entity you are answering three questions:
- What is this? — the business concept (orders, customers, products, locations)
- What makes a row unique? — the granularity key (primary key column(s))
- What columns should be exposed? — the initial attribute mapping from source columns
This skill focuses on the entity shell: source, key, and attribute mapping. Use
attribute-creationto add calculated attributes andrelation-creationto wire up joins afterwards — see After Validating: Hand Off to relation-creation.
Creation Methods
Quick Import: import_tables
Use import_tables to quickly import one or more data warehouse tables into the semantic model.
Each table becomes an entity with its columns automatically mapped as attributes. This is the fastest way to bootstrap entities when you don't need custom YAML.
Parameters:
tables— List of fully qualified table names in the format<database>.<schema>.<table>
Best for: bulk imports, quick prototyping, or when the default column-to-attribute mapping is sufficient.
Primary: create_entity (Recommended)
Unlike metrics and attributes, entity creation always requires YAML — there is no simplified single-expression API. create_entity is the preferred MCP tool because it creates both the entity and its dataset in a single operation.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 177 lines · 43 tokens per session scan A 74b3d85d89e4
entity-creation is a skill published in the GitHub repository honeydew-ai/honeydew-ai-coding-agents-plugins (39 stars, last pushed 10d ago), licensed Apache-2.0. It adds 43 tokens to every session and 1,860 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
data-charts-tako
Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
browse-and-evaluate
Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
render-airdrop-carousel
Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an…
render-3d-product-showcase
Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the brand-color canvas, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at…
telnyx-voice-advanced-curl
Advanced call control features including DTMF sending, SIPREC recording, noise suppression, client state, and supervisor controls. This skill provides REST API (curl) examples.