diff --git a/README.md b/README.md
index c964542..358ca14 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@ KQL CLI — query Azure Data Explorer (Kusto) from the command line.
 Like `jq` for JSON, but for Kusto/KQL. Run raw KQL, keep a git-versioned library
 of parameterized queries, and pipe results straight into your shell.
 
+![kq demo](docs/demo.gif)
+
 ## Installation
 
 ```bash
diff --git a/docs/LAUNCH_POST.md b/docs/LAUNCH_POST.md
new file mode 100644
index 0000000..4492ad5
--- /dev/null
+++ b/docs/LAUNCH_POST.md
@@ -0,0 +1,118 @@
+# Launch post drafts
+
+Three formats below: a blog/dev.to post, short Reddit/forum variants, and a
+one-line social post. Pick per venue; they say the same thing at different
+lengths.
+
+---
+
+## A) Blog / dev.to — "I built jq for Kusto"
+
+**Title:** I built `jq` for Kusto — a tiny CLI for querying Azure Data Explorer
+
+I run a lot of KQL against Azure Data Explorer, and I kept hitting the same
+friction: the web UI is great for exploring but terrible for automation, and
+`az kusto` isn't built for quick, pipeable, everyday queries. I wanted the thing
+`jq` is for JSON — small, fast, lives in the terminal, composes with pipes.
+
+So I built **`kq`**.
+
+```bash
+pip install kql-cli   # the command is `kq`
+
+kq config set default_cluster https://mycluster.kusto.windows.net
+kq config set default_database mydb
+kq auth login
+
+kq "MyTable | take 5"
+kq "MyTable | summarize count() by bin(Timestamp, 1h)" -f json | jq .
+```
+
+The part I actually care about most is **saved, git-versioned queries**. You
+write parameterized queries in YAML and run them by name:
+
+```yaml
+# ~/.config/kq/queries/ops.yaml
+queries:
+  - name: errors
+    description: Recent errors for a service
+    parameters:
+      - {name: service, required: true}
+      - {name: hours, default: "24"}
+    query: |
+      Traces
+      | where Timestamp > ago({hours}h)
+      | where Service == '{service}'
+      | where Level == 'Error'
+      | order by Timestamp desc
+```
+
+```bash
+kq run ops.errors checkout 6
+```
+
+Queries resolve from a project-local `./.kq/`, then your user queries, then
+bundled examples — so a repo can ship its own query library, and your personal
+queries never get clobbered by an update.
+
+A few other things it does:
+
+- **Auth that just works** — service principal → Azure CLI → cached device code,
+  with ~90-day silent refresh (handy on WSL/headless).
+- **`table` / `json` / `csv`** output — the JSON pipes straight into `jq`.
+- **Query safety levels** (`safe` / `caution` / `dangerous`) to keep expensive
+  full-table scans honest.
+- **Plays nicely with LLM coding agents** — clean, deterministic output.
+
+It's MIT-licensed, tested on Python 3.9–3.13, and on PyPI as `kql-cli`.
+
+Repo: https://github.com/cptfinch/kq
+
+If you work with Kusto/ADX, I'd love feedback — especially on what saved-query
+patterns you'd want built in.
+
+---
+
+## B) Reddit / Hacker News "Show" variants
+
+**Title options**
+- Show: kq — jq for Kusto/KQL (query Azure Data Explorer from the CLI)
+- I built a small CLI for querying Azure Data Explorer (like jq, but for KQL)
+
+**Body (r/AZURE, r/dataengineering, r/kusto):**
+
+I kept wanting a `jq`-style tool for KQL — something small and pipeable for
+querying Azure Data Explorer from the terminal, instead of the web UI or
+`az kusto`. So I made `kq`.
+
+- `kq "MyTable | take 5"` for raw KQL, `-f json|csv` for output
+- Saved, parameterized queries in YAML that you can git-version per project
+- Auth chain: service principal → Azure CLI → cached device code (~90-day refresh)
+- Query safety levels to flag expensive scans
+
+`pip install kql-cli` (the command is `kq`). MIT, tested on 3.9–3.13.
+
+https://github.com/cptfinch/kq
+
+Curious what saved-query patterns people would find useful — and how others are
+scripting against ADX today.
+
+---
+
+## C) One-liner (X / Mastodon / LinkedIn)
+
+`kq` — jq, but for Kusto/KQL. Query Azure Data Explorer from the terminal: raw
+KQL, git-versioned saved queries, json/csv output, sane auth.
+
+`pip install kql-cli` · MIT · https://github.com/cptfinch/kq
+
+---
+
+## Posting notes
+
+- Best-fit communities: r/AZURE, r/dataengineering, r/kusto, the Azure Data
+  Explorer community, and Show HN.
+- Post *after* PyPI is live so `pip install kql-cli` works from the first click.
+- The README demo GIF (`docs/demo.gif`) is worth embedding in the dev.to post
+  too — a moving demo roughly doubles conversion.
+- Lead with the `jq` analogy every time; it's the fastest way people "get it."
diff --git a/docs/RELEASE_NOTES_v1.0.0.md b/docs/RELEASE_NOTES_v1.0.0.md
new file mode 100644
index 0000000..05ae02f
--- /dev/null
+++ b/docs/RELEASE_NOTES_v1.0.0.md
@@ -0,0 +1,56 @@
+# kq v1.0.0 — first public release
+
+Paste this into the GitHub Release body when tagging `v1.0.0`.
+
+---
+
+`kq` is a KQL CLI for Azure Data Explorer (Kusto). Like `jq` for JSON, but for
+KQL — run raw queries, keep a git-versioned library of parameterized queries,
+and pipe results straight into your shell.
+
+## Install
+
+```bash
+pip install kql-cli
+```
+
+The command is `kq`. (The PyPI package is `kql-cli` because `kq` was already
+taken on PyPI by an unrelated project.)
+
+## Quick start
+
+```bash
+kq config set default_cluster https://mycluster.westeurope.kusto.windows.net
+kq config set default_database mydb
+kq auth login
+
+kq "MyTable | take 5"                 # raw KQL
+kq "MyTable | take 5" -f json         # or -f csv
+kq list                               # saved queries
+kq run examples.sample MyTable 10     # run a saved query
+```
+
+## Highlights
+
+- **Raw KQL and saved queries** — run KQL directly, or curate reusable,
+  parameterized queries in YAML and run them by name.
+- **Git-versionable query libraries** — queries resolve from `./.kq/` (project),
+  `~/.config/kq/queries/` (user), then bundled examples. Your queries are never
+  overwritten by updates.
+- **Multi-cluster config** — named clusters, XDG-compliant config in
+  `~/.config/kq/config.yaml`.
+- **Flexible auth** — service principal → Azure CLI → cached device code, with
+  ~90-day silent token refresh (great for WSL/headless).
+- **Output formats** — `table`, `json`, `csv`.
+- **Query safety levels** — mark queries `safe` / `caution` / `dangerous` to
+  keep expensive full-table scans honest.
+- **LLM-native & Unix-friendly** — clean, pipeable output that works well with
+  Claude Code, Copilot, scripts, and automation.
+
+## Quality
+
+- Test suite + `ruff` linting.
+- GitHub Actions CI across Python 3.9–3.13.
+- Published via PyPI Trusted Publishing (OIDC — no stored tokens).
+
+**Full changelog:** see [CHANGELOG.md](../CHANGELOG.md).
diff --git a/docs/demo.cast b/docs/demo.cast
new file mode 100644
index 0000000..36a6a04
--- /dev/null
+++ b/docs/demo.cast
@@ -0,0 +1,98 @@
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diff --git a/docs/demo.gif b/docs/demo.gif
new file mode 100644
index 0000000..5eb8fb8
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