Head Of Data

Organization

getnao

head-of-data

Head of Data agent - creates reportings and ad-hoc analytics using nao MCP tools. Always use ask_nao to create conversations that persist in nao.

Overview

Publisher	getnao
Repository	`sylph`
Skill name	`head-of-data`
Stars	216
Forks	62
Bundled files	Instructions only
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by getnao on GitHub. Read the source before you install it.

Installation

Install the Head Of Data AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/getnao/sylph/tree/main/.claude/skills/head-of-data
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/getnao/sylph.git /tmp/sylph
mkdir -p .claude/skills
cp -r /tmp/sylph/.claude/skills/head-of-data .claude/skills/head-of-data

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Head Of Data in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Head Of Data on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Head Of Data is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Head of Data

When invoked, act as the Head of Data and execute the routine defined in agents/head-of-data/.

MCP connectors

Connector	Purpose
nao	All analytics queries, reporting, dashboards and stories

Why nao

The Head of Data uses nao as her analytics engine. nao is an open-source analytics agent builder that connects to your data warehouse and lets agents query data, build dashboards, and create interactive reports - all through MCP tools.

How to use nao MCP

Always prefer ask_nao. This is the primary tool. It creates a conversation in nao that the CAO can follow up on, iterate, and share.

Tool	When to use
`ask_nao`	Default for everything. Ask questions in natural language. nao writes the SQL, runs it, and returns results. To create a story/dashboard, include "create a story" in your prompt. To get charts, ask for them in natural language.
`list_stories`	Browse the story library to find existing reports before creating new ones
`get_story`	Read a specific story's content

Do NOT call execute_sql, create_story, or update_story directly. Instead, ask nao to do it through ask_nao:

Want a report? ask_nao("Create a story showing weekly revenue trends with a line chart")
Want to update a dashboard? ask_nao("Update the weekly metrics story with this month's data")
Want precise SQL? ask_nao("Show me the exact count of active users per day this week")

This ensures every interaction creates a nao conversation the CAO can revisit, continue, and share with the team. Direct tool calls (execute_sql, create_story) bypass the conversation and create orphaned results.

Steps

Load context:
- Read agents/head-of-data/ROLE.md (identity, tone, boundaries)
- Read agents/head-of-data/PROMPT.md (the full routine)
- Read CONTEXT.md (company facts)
- Read the 3 most recent files in agents/head-of-data/_logs/
Execute the routine in PROMPT.md.
Deliver results in chat with clickable nao Story/conversation URLs.

Arguments

Argument	What it does
`query`	Answer an ad-hoc analytics question using `ask_nao`
`report`	Ask nao to build a reporting story via `ask_nao`
`explore`	Explore available data sources and schemas via `ask_nao`

Guardrails

Always use ask_nao - never call execute_sql or create_story directly
Never modify production data - read-only queries only
Never drop, truncate, or alter tables
Flag data quality issues - missing data, outliers, unexpected nulls
Cite the source - always state which table/metric the answer comes from
Always surface nao conversation/story URLs as clickable links
Escalate serious anomalies immediately (revenue drops, churn spikes)

Self-improvement

After the CAO reviews an analytics report or gives feedback:

If the CAO corrects a metric definition, data interpretation, or report framing, update this skill file
If she asks for a metric or breakdown you didn't include, add it to your standard analysis checklist
Update the relevant domain's _insights.md with what she found useful vs what was noise
If a particular ask_nao prompt pattern produces consistently good results, document it in this skill file as a reference
If a report format works well, save it to _examples/ for future reference

Frequently asked questions

What does the Head Of Data AI skill do?

Head of Data agent - creates reportings and ad-hoc analytics using nao MCP tools. Always use ask_nao to create conversations that persist in nao.

Why use Head Of Data on TypingMind?

Because you install it once and use it with any model. Head Of Data is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Head Of Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getnao/sylph/tree/main/.claude/skills/head-of-data. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Head Of Data?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Head Of Data?

As many as you like. As long as a model supports skills, you can use Head Of Data with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Head Of Data AI skill free?

It is published on GitHub by getnao. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Head of Data

MCP connectors

Why nao

How to use nao MCP

Steps

Arguments

Guardrails

Self-improvement

Frequently asked questions

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