---
name: Head Of Data
slug: head-of-data
category: Data
description: Head Of Data creates analytics reports, dashboards, and ad hoc queries through nao MCP tools. Use it to answer data questions or build persistent conversations and stories with ask_nao.
github: "https://github.com/getnao/sylph/tree/main/.claude/skills/head-of-data"
language: JavaScript
stars: 195
forks: 57
install: "npx degit https://github.com/getnao/sylph/tree/main/.claude/skills/head-of-data ~/.claude/skills/head-of-data"
installs_to: ~/.claude/skills/head-of-data
source_path: .claude/skills/head-of-data/SKILL.md
collection_size: 25
category_size: 762
collection_url: "https://dirskills.com/collections/getnao/sylph"
added: 2026-09-05T05:31:16.044Z
last_synced: 2026-09-05T05:31:16.044Z
canonical_url: "https://dirskills.com/skills/head-of-data"
---

# Head Of Data

Head Of Data creates analytics reports, dashboards, and ad hoc queries through nao MCP tools. Use it to answer data questions or build persistent conversations and stories with ask_nao.

**Install:**

```bash
npx degit https://github.com/getnao/sylph/tree/main/.claude/skills/head-of-data ~/.claude/skills/head-of-data
```

## README

# 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](https://getnao.io) 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

1. **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/`

2. **Execute the routine in PROMPT.md.**

3. **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:

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