streamsnow 0.9.1

Build, govern, and ship Streamlit-in-Snowflake apps with AI.
The open-source Claude Code plugin and CLI that turns an idea into a governed, reviewed dashboard running in Snowflake, without learning the platform's traps the hard way.

Quickstart · Docs · Skills · CLI reference · Principles · Discussions · Changelog

_{Offline demo: scaffold a governed repo, hit the validate-app gate, and preview a dashboard. With Claude Code, /build-app drives these steps and /ship-app opens the PR; CI deploys to Snowflake.}

Quick start. In the folder for your Snowflake apps, run claude plugin marketplace add --scope project kyle-chalmers/streamsnow and claude plugin install --scope project streamsnow@streamsnow, then type /reload-plugins and /onboard in Claude Code. No Claude Code? uvx streamsnow init. Using another agent? Install with your coding agent.

Status: beta, functional. The CLI and the Claude Code plugin are CI-green for both runtimes and both deploy sources, and published on PyPI. APIs may still evolve toward 1.0; Versioning and stability says what is already promised.

Mission

StreamSnow aims to let a data team build and ship, quickly and safely, Streamlit-in-Snowflake apps that load fast, can be trusted, and help people make decisions, by turning production lessons into scaffolding, checks, and guidance that people and AI sessions can follow without having to remember them.

Vision

A data professional, with or without an AI assistant, can take a dashboard from idea to a governed, verified deployment in Snowflake without learning the platform's traps the hard way; a reviewer with Snowsight can re-run the SQL behind the numbers it shows; and the people it's built for can open it, understand it, and act on it without a walkthrough.

This is for you if:

• ✅ you want to build the most useful and beautiful dashboards of your life
• ✅ you want to eliminate the time you spend dragging and dropping in traditional BI tools
• ✅ you want analytics to stop being a bottleneck at your company
• ✅ you run, or will run, more than one Streamlit app in Snowflake with more than one author
• ✅ you want Claude Code sessions and humans held to the same governance rules
• ✅ you want a reviewer to re-run a dashboard's SQL in Snowsight without reading Python
• ❌ you host Streamlit outside Snowflake, or you need a scheduler or a data catalog (StreamSnow does neither)
• ❌ your dashboards are for people without Snowflake logins, out of the box (possible with customization)

Prerequisites: a Snowflake account, an AI coding agent, and either knowing or being a Snowflake administrator (the one-time setup is in Deploy setup).

Principles: every change is judged against nine principles, from one implementation, many consumers to design is a default, not a gate.

What Claude can and can't see

StreamSnow asks Claude to set up Snowflake access, CI and deploy secrets on your behalf. Here is exactly what that means for your credentials.

• Claude never sees a password, private key or token. Sign-ins happen in your browser, and StreamSnow never asks for, stores or handles a Snowflake password.
• The CI key goes from a file on your machine to GitHub without passing through Claude. streamsnow ci-key create makes the key pair in ~/.streamsnow-ci and prints only file names and a fingerprint. streamsnow ci-key push hands each secret to the GitHub CLI on standard input, never on the command line, and prints only names.
• Save a copy of the private key somewhere safe. Put ~/.streamsnow-ci/streamsnow_ci_rsa_key.p8 in a password manager or similar store yourself; Claude never opens it. If it is ever lost, make a new pair and re-run the admin script (rotating the key).
• Snowflake gets only the public half of the key. It goes into the admin script, which you or your Snowflake admin run. Claude never runs it and creates no Snowflake objects itself.
• Claude's tools are blocked from the key directory. The plugin's key guard (hooks/secret_guard.py) denies any read, search, edit or shell command that points at it, apart from plain streamsnow ci-key and streamsnow deploy-setup commands.
• Setup queries are read-only. The setup flow reads your account with SHOW and SELECT queries only, and never prints connection files or SNOWFLAKE_* values.

The limits, stated plainly: Claude runs as your user account, so the key guard is a backstop, not a sandbox, and it runs only inside Claude Code. The full detail is in SECURITY.md.

Install with your coding agent

Point any coding agent (Claude Code, Codex, Cursor, Gemini CLI, and others) at this repo and say: "Read the install prompt in github.com/kyle-chalmers/streamsnow and follow it." Or paste the prompt in yourself:

Install StreamSnow (https://github.com/kyle-chalmers/streamsnow) for me at the
project level: enable the plugin and install the skills for this repo only,
never at the user level. Confirm with me before installing anything, and stop at
each question you cannot answer on my behalf.

1. Work in the git repo for my Snowflake apps. Ask me which folder if unsure; if it
   is new, create it and run `git init`. Run every command below from its root.

2. If you are Claude Code: run
   `claude plugin marketplace add --scope project kyle-chalmers/streamsnow` and then
   `claude plugin install --scope project streamsnow@streamsnow`. Both record the
   plugin in this repo's .claude/settings.json, not my user settings. Tell me to
   type `/reload-plugins` (no restart needed) and then `/onboard`. Stop
   there; that skill does the rest.

3. Any other agent: make sure `uv` is installed, then run `uv tool install streamsnow`
   and confirm `streamsnow --version` answers (the CLI is a command on my PATH; the
   skills call it by name). Run `streamsnow doctor` and fix each failing required
   check one at a time, re-running doctor after each fix.

4. If the repo already has a `streamsnow.config.yaml`, it is set up: run `streamsnow doctor`,
   and run `streamsnow init --no-starter-app` only if its `repo-files` row lists missing files.
   Otherwise, if the repo already has Streamlit apps, read
   https://github.com/kyle-chalmers/streamsnow/blob/main/skills/onboard/adopt.md and
   follow that instead of scaffolding. Otherwise set up with `streamsnow init --no-starter-app`.
   Its wizard asks five questions. Answer what you can first with read-only SHOW queries
   over whatever Snowflake access I already have (my default snow connection, a Snowflake
   MCP server, a dbt profile), ask me only what you could not settle, then pass the
   confirmed answers as flags (see `streamsnow init --help`). If you cannot, hand the
   wizard to me.

5. Run `streamsnow agent-skills install --agent codex` (repo scope, the default; never
   `--scope user`). It copies the skills into this repo's .agents/skills, which Codex
   reads; any other agent can open .agents/skills/onboard/SKILL.md directly. Then
   follow onboard, and then build-app to build my first app.

Rules: never ask me for a Snowflake password or key in chat; if I choose, you may set
up my snow connection with flags, and I approve the sign-in in my browser. Never run
the admin SQL that `streamsnow deploy-setup --admin` prints; prepare it for me or my
Snowflake admin.

Only Claude Code and Codex are tested. Prefer to type the steps yourself? See Quickstart, and Use with other agents for what differs outside Claude Code.

How the skills fit together

How the repos fit together

Both diagrams are Excalidraw files in docs/images/; edit the .excalidraw source at excalidraw.com and re-export the PNG with scripts/readme_media.

What it is

StreamSnow is a hybrid of two things that work together:

1. A streamsnow CLI (PyPI) — scaffolds a governed Streamlit-in-Snowflake monorepo, runs an interactive setup wizard, renders the CI, pre-commit hooks and branding your repo needs, and runs the governance checks (from the installed package, so your repo carries no copied tool code).
2. A Claude Code plugin (marketplace) — ships the skills and hooks that turn Claude Code into a domain expert for this stack: /build-app (the front door), /preview-app, /validate-app, /review-app, /ship-app, and more.

Think a Claude Code skill pack fused with an installable system + setup. The CLI gives you the substrate; the plugin gives Claude the playbook. A single streamsnow.config.yaml is the source of truth both read from.

Why

Building Streamlit apps on Snowflake well means getting a hundred small things right: caching with TTLs, parameterized SQL that survives the deployed Go driver, runtime selection (container vs. warehouse), schema access guardrails, a deploy pipeline, branding, and review discipline. StreamSnow encodes those as executable guardrails — pre-commit + CI gates, scaffolding templates, and Claude Code skills — so every developer (and every Claude session) follows the same rules and ships safely.

Without StreamSnow / with StreamSnow

Every guardrail exists because something went wrong in a real production fleet (Production lessons has the full story of each).

Two things you choose

StreamSnow treats two axes as first-class, configurable options:

Quickstart

Two lanes; pick the one that matches how you work. Both end at the same governed repo, and both need Python 3.11+, uv, and git (uvx streamsnow doctor tells you what is missing).

With Claude Code (recommended)

From the root of your apps repo, install the plugin at project scope (it is recorded in the repo's .claude/settings.json, not your user settings):

claude plugin marketplace add --scope project kyle-chalmers/streamsnow
claude plugin install --scope project streamsnow@streamsnow

Then, in a Claude Code session in that repo, load it without restarting and start setup:

/reload-plugins
/onboard

/reload-plugins picks up the plugin's skills and hooks in the running session. StreamSnow's one-line session-start message first appears in your next session.

/onboard gets your machine, repo and Snowflake account ready, in four stages, and says what it is doing at every step:

1. Check and prepare. It works out what is already set up, reads your Snowflake account with read-only queries over whatever access you have (a snow connection, a Snowflake MCP server, a dbt profile), and installs any missing tools after one approval.
2. One round of questions. Clickable choices for what it could not work out: the five setup answers, your git name if it is missing, and who runs the Snowflake admin script.
3. Build. The config and the governed repo files (AGENTS.md, CLAUDE.md, pre-commit hooks, CI, .gitignore, README), only after you confirm.
4. Finish. The CI key, the admin script (copied for you to run in Snowsight, or written up for your admin), and the deploy secrets.

It ends "ready to build and preview" (next: /build-app) or "ready to deploy". Your part: approve installs, answer one round of questions, approve sign-ins in your browser, and run the admin script in Snowsight if you are the admin. In a repo that already has Streamlit apps it maps onto them and writes a MIGRATION.md, never scaffolding over you. Re-run /onboard any time to check.

CLI only

uv tool install streamsnow           # persistent `streamsnow` on your PATH
mkdir my-snowflake-apps && cd my-snowflake-apps
streamsnow init                      # 5-question wizard, then a governed scaffold
# or skip the prompts: streamsnow init --runtime warehouse --account <locator> \
#   --database ANALYTICS --schemas MARTS,REPORTING --deploy-source stage-copy
snow connection add --connection-name <name> --account <locator> \
  --user <you> --authenticator externalbrowser --default   # init prints the exact command
uv tool install pre-commit && pre-commit install
streamsnow validate-app example-dashboard   # FAILS on the starter placeholders until you replace them
uv venv --python 3.11 && uv pip install -e apps/example-dashboard   # container runtime
streamsnow preview example-dashboard

validate-app fails on purpose until you repoint the starter query (queries/example_metric.sql) and the review window in sql_review/index.yaml at your own table and replace the sample numbers in pages/overview.py; every other check passing is what proves the scaffold is whole.

On the warehouse runtime an app has environment.yml instead of pyproject.toml, so install its packages directly (init and streamsnow preview print the exact line).

One connection store: st.connection("snowflake") reads the snow CLI's default connection locally, so the per-app secrets.toml is an optional override, not a second place to type the same values.

Upgrading

The two halves upgrade separately, and the plugin half does not pick up hook or skill changes on its own — an installed copy stays at the version it was installed at until you reinstall it.

claude plugin list                                              # installed plugin version
claude plugin uninstall --scope project streamsnow@streamsnow
claude plugin install --scope project streamsnow@streamsnow    # then /reload-plugins in Claude Code

uv tool upgrade streamsnow               # the CLI
streamsnow update                        # dry-run: governance files the new templates would change
streamsnow update --apply                # re-render AGENTS.md, CLAUDE.md, hooks, CI, deploy.yml

Generated CI and deploy workflows pin streamsnow>=0.9,<0.10; bump the pin with update --apply when you move to a new minor release (before 1.0, minors can break). claude plugin details streamsnow@streamsnow lists the 8 skills below.

The skills

One front door plus focused verbs — each skill's SKILL.md stays under 80 lines, with depth in per-skill reference files:

Use with other agents

The skills are plain SKILL.md folders in the open Agent Skills format, so a coding agent other than Claude Code can follow them. OpenAI Codex CLI 0.157.1 is the only one tested. The CLI installs them where Codex looks:

streamsnow agent-skills install --agent codex               # <repo>/.agents/skills; commit it
streamsnow agent-skills list --agent codex                  # what is installed, and from which version

SQL review (redesigned in 0.8)

Every page of an app gets SQL a person can run: apps/<slug>/sql_review/NN_<page>.sql, one section per metric in on-screen order, each runnable on its own (cursor + Cmd/Ctrl+Enter in DataGrip, or pasted into Snowsight) with its review window in its own params CTE. The files are generated from sql_review/index.yaml, which lists each page's metrics and the app query behind each, and verified by an import-free gate (streamsnow sql-review check): provenance digests, the review_value("<key>", value) markers that tie each visual in page code to its section, sqlfluff lint and comment rules for the app's queries, and a folder of maintained DDL (app_specific_reporting_objects/) for views built just for the app. Drift, hand edits, marker mismatches and lint always fail the gate; whether an uncovered page or query fails or warns is your repo's call — sql_review: {coverage: warn | fail} in streamsnow.config.yaml (default warn, so an adopting fleet backfills on its own schedule). A person with nothing but a SQL editor can trace a covered visual back to the data and confirm it — see Auditing a visual. 0.8.0 replaced the 0.6/0.7 manifest format with no automatic migration (the same page has the upgrade steps).

/sql-review <slug> is the live review. streamsnow sql-review probe and run check every object, grant and DDL file and run every section against Snowflake as aggregates (row counts, totals and a hash, never rows), under the app's role with secondary roles off. Reviewer agents judge the SQL and must cite those results; a verifier drops what the evidence does not support; streamsnow sql-review log writes sql_review/review_log/YYYY-MM-DD_<sha>.md with a sign-off block for a person. bench proves an optimization returns the same result before proposing it.

Make it yours: repo overlays

The skills are generic procedures; your org's knowledge layers on top without forking them. Commit .streamsnow/overlays/<skill>.md files and every skill reads its overlay first — extra steps, local failure signatures, environment specifics, explicit overrides. Plugin upgrades never touch them; overlays may not skip mandatory gate invocations, and the coded gates (hooks, CI, pre-commit) run outside skill prose entirely. See skills/_shared/overlays.md.

Hooks, in full

Trust demands transparency: this plugin runs hooks, so here is every one of them. All are stdlib-only, make no network calls, never write outside the repo (plus one best-effort dedupe state file in $TMPDIR, so the review nudge fires once per state, not every turn), and fail open, so a hook error never blocks your session. The one exception is the key guard, which denies rather than asks, and denies even if it hits an error on a call that names the key directory.

All hooks except the key guard are repo-gated on streamsnow.config.yaml (zero cost in unrelated repos; the SessionStart /onboard nudge above is the one line that also appears in a repo without a config) and declare explicit timeouts so a hung hook can never stall a session. To turn them off, disable the plugin (claude plugin disable streamsnow). Hook additions do not reach installed copies automatically — see Upgrading.

The browser tool

The skills click through each page of your running app and screenshot it with Microsoft's Playwright CLI, pinned to an exact version and run through npx only when a skill walks your app, so you see a broken page before it ships. There is no MCP server to start. Unlike the hooks it does use the network: npx downloads the pinned package from npm the first time, and the CLI downloads its own browser once. It needs Node.js 20+; without Node the walkthroughs are skipped and everything else works. streamsnow doctor checks Node, and /onboard downloads the CLI and its browser ahead of time.

How it's organized

streamsnow/            the PyPI package — CLI, config, policy, scaffolder, tools
  ├── cli.py           every command (see docs/cli-reference.md)
  ├── config.py        typed + validated streamsnow.config.yaml model
  ├── policy.py        schema allow/deny single source of truth
  ├── scaffolder.py    renders a governed repo from config
  ├── deploy.py        deploy-setup and deploy-sql
  ├── verify.py        verify-deploy
  ├── ci_key.py        ci-key create / push
  ├── agent_skills.py  agent-skills (Codex and other agents)
  ├── _templates/      the Jinja scaffold templates (repo/ + app/)
  └── tools/           governance checks + engines (schema refs, security,
                       caching, dependency vulns, tombstones, path leaks,
                       sql_review generator, review gate/loop, migrate, preview)
.claude-plugin/        Claude Code plugin manifest + marketplace
skills/  hooks/        Claude Code plugin surface (8 skills, incl. onboard/; hooks)
docs/  examples/       guides + a runnable no-Snowflake example app
scripts/               maintainer tools (docs link check, README media)

The streamsnow Python package is the single source of truth for tool logic: the CLI, the Claude Code plugin, pre-commit, and CI all call the same code — one implementation, many consumers.

Documentation

• Getting started — run the example with no Snowflake, then scaffold and preview your own governed app.
• CLI reference — every command, flag and check, with exit codes and JSON output.
• Principles — the nine rules every change is judged against, and where each one shows up.
• Data discovery — find tables and wire queries inside the schema-access guardrails.
• Deploying — ship apps to Snowflake on merge, for both deploy sources.
• Deploy setup — the one-time Snowflake objects and CI secrets the pipeline needs.
• Switching to Git repository: when to deploy from a Snowflake GIT REPOSITORY instead of a stage, and how to switch.
• Auditing a visual — the five-minute runbook for confirming any dashboard number against the warehouse, no code required.
• Production lessons — the incidents behind the guardrails, genericized.
• Troubleshooting — numbered symptom / cause / fix entries for the first-run and deploy failures people actually hit.
• Official Snowflake docs, by topic — every external docs link the toolkit relies on, with scope, retrieved date, and where StreamSnow deliberately differs.
• Distribution — how StreamSnow ships (PyPI CLI + plugin) and why there's no separate copy-paste kit.
• Migrating a consumer repo — bring a repo with home-grown skills onto the plugin (skill map + incremental path).
• Versioning and stability — what counts as a breaking change, the deprecation policy, and the path to 1.0.

Feedback and community

• Questions and ideas: Discussions.
• Bugs and scoped feature requests: open an issue with one of the forms. Issues are triaged automatically, and the ones the maintainer approves are often implemented by an AI agent and reviewed before merge (how issues move).
• Contributing: CONTRIBUTING.md, including the AI-assisted contribution policy. Everyone agrees to the Code of Conduct.
• Security: report privately, per SECURITY.md.

Star history

If StreamSnow saves you a production incident (or a week of dragging boxes around a BI tool), ⭐ star the repo so you can find it again when you ship your next app, and so other data teams can find it too.

License

MIT © Kyle Chalmers

StreamSnow is an independent open-source project and is not affiliated with or endorsed by Snowflake Inc., Streamlit, or Anthropic.