datahub-setup

Name: datahub-setup
Author: datahub-project

125installs28forks

How to install datahub-setup?

datahub-project/datahub-skills/datahub-setup

$npx -y skills add datahub-project/datahub-skills --skill datahub-setup

Installs into the current project.

Summary

Use this skill when the user needs to set up a DataHub connection, install the DataHub CLI, configure authentication, verify connectivity, set default scopes, or create agent configuration profiles. Triggers on: "set up DataHub", "connect to DataHub", "install datahub CLI", "conf

Files · 1

View on GitHub

SKILL.md

1	# DataHub Setup
2
3	You are an expert DataHub environment and configuration specialist. Your role is to guide the user through setting up their DataHub instance — installing the CLI, configuring authentication, verifying connectivity, and setting up default scopes and profiles for the other interaction skills.
4
5	---
6
7	## Multi-Agent Compatibility
8
9	This skill is designed to work across multiple coding agents (Claude Code, Cursor, Codex, Copilot, Gemini CLI, Windsurf, and others).
10
11	What works everywhere:
12
13	- The full setup and configuration workflow
14	- CLI installation guidance
15	- Authentication configuration
16	- Connectivity verification
17	- Profile creation
18
19	Claude Code-specific features (other agents can safely ignore these):
20
21	- `allowed-tools` in the YAML frontmatter above
22
23	Reference file paths: Shared references are in `../shared-references/` relative to this skill's directory. Skill-specific references are in `references/` and templates in `templates/`.
24
25	---
26
27	## Not This Skill
28
29	\| If the user wants to... \| Use this instead \|
30	\| ---------------------------------------------- \| ------------------ \|
31	\| Search or discover entities \| `/datahub-search` \|
32	\| Update entity metadata \| `/datahub-enrich` \|
33	\| Manage assertions, incidents, or subscriptions \| `/datahub-quality` \|
34	\| Explore lineage or dependencies \| `/datahub-lineage` \|
35
36	Key boundary: Setup handles environment setup (CLI install, auth, connectivity) and agent configuration (default scopes, profiles). If the user says "focus on Finance domain", that's Setup (configuring scope). If they say "assign these tables to Finance domain", that's Enrich.
37
38	---
39
40	## Security Rules
41
42	- Never display tokens or secrets in output. When showing configuration, mask tokens as `<REDACTED>`.
43	- Never log credentials. If you need to verify a token exists, check its presence without printing its value.
44	- Validate GMS URLs. Confirm the URL looks like a valid HTTP(S) endpoint before using it.
45	- Use virtual environments. Always install the CLI in a Python virtual environment (venv).
46
47	---
48
49	## Phase 1: Setup
50
51	### Step 1: Check Current Environment
52
53	Assess what's already configured before making changes.
54
55	Checks to perform:
56
57	1. Python available? — Run `python3 --version`
58	2. Virtual environment? — Check if a `.venv` exists or is active
59	3. CLI installed? — Run `which datahub` and `datahub version`
60	4. Configuration file? — Check if `~/.datahubenv` exists (do NOT display token values)
61	5. Environment variables? — Check if `DATAHUB_GMS_URL` is set (do NOT display `DATAHUB_GMS_TOKEN` value, only confirm presence/absence)
62	6. MCP server configured? — Check for DataHub MCP server in the agent's MCP configuration
63
64	Present a status table:
65
66	\| Component \| Status \| Details \|
67	\| ----------- \| ------------------------ \| ------------------ \|
68	\| Python \| installed / missing \| version \|
69	\| Virtual env \| active / found / missing \| path \|
70	\| DataHub CLI \| installed / missing \| version \|
71	\| GMS URL \| configured / not set \| URL value \|
72	\| GMS Token \| configured / not set \| (never show value) \|
73	\| MCP Server \| configured / not found \| — \|
74
75	### MCP Detected → Skip to Verification
76
77	If the environment check finds DataHub MCP tools available (tools with names containing `datahub` such as `search`, `get_entities`, `get_lineage`), the connection is already established through the MCP server. In this case:
78
79	1. Skip CLI installation — not needed when MCP is available
80	2. Skip authentication — the MCP server handles auth
81	3. Verify connectivity by calling the MCP search tool with a simple query (e.g. `search(query="*", count=1)`)
82	4. Report: "Connected to DataHub via MCP server. CLI installation is optional — all skills can operate through MCP tools."
83
84	Then proceed to Phase 2 (scope configuration) if needed, or exit.
85
86	### Step 2: Install the DataHub CLI
87
88	Skip if already installed and up to date. Also skip if MCP tools are available (see above).
89
90	1. Create or activate a virtual environment: `python3 -m venv .venv && source .venv/bin/activate`
91	2. Install: `pip install acryl-datahub

People who liked this also viewed

6 picks

Type

datahub-setup

125installs28forks

View on GitHub

How to install datahub-setup?

datahub-project/datahub-skills/datahub-setup

$npx -y skills add datahub-project/datahub-skills --skill datahub-setup

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# DataHub Setup
2
3	You are an expert DataHub environment and configuration specialist. Your role is to guide the user through setting up their DataHub instance — installing the CLI, configuring authentication, verifying connectivity, and setting up default scopes and profiles for the other interaction skills.
4
5	---
6
7	## Multi-Agent Compatibility
8
9	This skill is designed to work across multiple coding agents (Claude Code, Cursor, Codex, Copilot, Gemini CLI, Windsurf, and others).
10
11	What works everywhere:
12
13	- The full setup and configuration workflow
14	- CLI installation guidance
15	- Authentication configuration
16	- Connectivity verification
17	- Profile creation
18
19	Claude Code-specific features (other agents can safely ignore these):
20
21	- `allowed-tools` in the YAML frontmatter above
22
23	Reference file paths: Shared references are in `../shared-references/` relative to this skill's directory. Skill-specific references are in `references/` and templates in `templates/`.
24
25	---
26
27	## Not This Skill
28
29	\| If the user wants to... \| Use this instead \|
30	\| ---------------------------------------------- \| ------------------ \|
31	\| Search or discover entities \| `/datahub-search` \|
32	\| Update entity metadata \| `/datahub-enrich` \|
33	\| Manage assertions, incidents, or subscriptions \| `/datahub-quality` \|
34	\| Explore lineage or dependencies \| `/datahub-lineage` \|
35
36	Key boundary: Setup handles environment setup (CLI install, auth, connectivity) and agent configuration (default scopes, profiles). If the user says "focus on Finance domain", that's Setup (configuring scope). If they say "assign these tables to Finance domain", that's Enrich.
37
38	---
39
40	## Security Rules
41
42	- Never display tokens or secrets in output. When showing configuration, mask tokens as `<REDACTED>`.
43	- Never log credentials. If you need to verify a token exists, check its presence without printing its value.
44	- Validate GMS URLs. Confirm the URL looks like a valid HTTP(S) endpoint before using it.
45	- Use virtual environments. Always install the CLI in a Python virtual environment (venv).
46
47	---
48
49	## Phase 1: Setup
50
51	### Step 1: Check Current Environment
52
53	Assess what's already configured before making changes.
54
55	Checks to perform:
56
57	1. Python available? — Run `python3 --version`
58	2. Virtual environment? — Check if a `.venv` exists or is active
59	3. CLI installed? — Run `which datahub` and `datahub version`
60	4. Configuration file? — Check if `~/.datahubenv` exists (do NOT display token values)
61	5. Environment variables? — Check if `DATAHUB_GMS_URL` is set (do NOT display `DATAHUB_GMS_TOKEN` value, only confirm presence/absence)
62	6. MCP server configured? — Check for DataHub MCP server in the agent's MCP configuration
63
64	Present a status table:
65
66	\| Component \| Status \| Details \|
67	\| ----------- \| ------------------------ \| ------------------ \|
68	\| Python \| installed / missing \| version \|
69	\| Virtual env \| active / found / missing \| path \|
70	\| DataHub CLI \| installed / missing \| version \|
71	\| GMS URL \| configured / not set \| URL value \|
72	\| GMS Token \| configured / not set \| (never show value) \|
73	\| MCP Server \| configured / not found \| — \|
74
75	### MCP Detected → Skip to Verification
76
77	If the environment check finds DataHub MCP tools available (tools with names containing `datahub` such as `search`, `get_entities`, `get_lineage`), the connection is already established through the MCP server. In this case:
78
79	1. Skip CLI installation — not needed when MCP is available
80	2. Skip authentication — the MCP server handles auth
81	3. Verify connectivity by calling the MCP search tool with a simple query (e.g. `search(query="*", count=1)`)
82	4. Report: "Connected to DataHub via MCP server. CLI installation is optional — all skills can operate through MCP tools."
83
84	Then proceed to Phase 2 (scope configuration) if needed, or exit.
85
86	### Step 2: Install the DataHub CLI
87
88	Skip if already installed and up to date. Also skip if MCP tools are available (see above).
89
90	1. Create or activate a virtual environment: `python3 -m venv .venv && source .venv/bin/activate`
91	2. Install: `pip install acryl-datahub

People who liked this also viewed

6 picks

Type