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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.
| Date | Stars |
|---|---|
| 2026-07-31 | 363 |
| 2026-08-04 | 363 |
| 2026-08-06 | 363 |
Today
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Momentum
15.0
growth rate 0.00%/day
# oneshot-gtm > Open-source GTM agent for technical founders. Pay-per-result. Signed receipts. Founder-led discipline encoded. Two surfaces: terminal CLI + local web dashboard, both backed by the same SQLite ledger. ```bash # Dashboard-only (published, no clone needed): bunx oneshot-gtm-server # opens http://127.0.0.1:3030 # Full install (CLI + dashboard, repo clone — see below): bun run cli -- init # one-time setup bun run cli -- ui # opens http://127.0.0.1:3030 ``` [](https://www.npmjs.com/package/@oneshot-agent/sdk) [](./LICENSE) [](https://bun.sh) [](https://www.typescriptlang.org) --- ## What this is A focused, opinionated wrapper around [OneShot](https://docs.oneshotagent.com) — a pay-per-use API toolbox for email, SMS, voice, deep research, person enrichment, browser automation, and website build, all settled per-call in USDC on Base with **cryptographically signed receipts** for every action. OneShot is the toolbox. `oneshot-gtm` is the **strategy wrapper**: it encodes the canonical PMF + founder-led-sales playbook (Mom Test, Sean Ellis 40%, Predictable Revenue, do-things-that-don't-scale, multichannel cadence, signed-receipt CAC) as a set of named _plays_ you actually run from the terminal or the dashboard. It's open source (MIT) so you can read every prompt, fork every play, and trust what's running. --- ## Two ways to use it ### Terminal — for power users + scripting ```bash bun run cli -- intel advise # interactive coach bun run cli -- discover icp interview-prep "your hypothesis" bun run cli -- find watch --once # poll all due triggers, enqueue candidates bun run cli -- find drain podcast-guest --dry-run # preview approved /queue rows bun run cli -- cadence advance # daily tick: poll inbox + fire follow-ups ``` ~30 commands across 9 groups. See `bun run cli -- --help` or jump to the [Command map](#command-map). ### Dashboard — for visibility + non-technical co-founders ```bash bun run cli -- ui # default: serves prebuilt React app on 127.0.0.1:3030 bun run cli -- ui --dev # vite hot-reload + API server in parallel bun run cli -- ui --port 4000 # custom port bun run cli -- ui --no-browser # don't auto-open ``` Eight pages, all reading the same `~/.oneshot-gtm/ledger.sqlite`: - **Home** — spend (7d / 30d), reply rate trend, in-flight cadences, recent receipts - **Queue** — triggers table (enable, edit JSON config, fire) + target queue (status + play filters, bulk approve). Per-play **Drain** opens a modal that hands off to `/run/<play>` with approved rows pre-loaded — every draft + lint flag streams live, and the latest draft persists on the queue row so you can re-read it later by expanding the row (subject + body + flags + receipt links). Per-row spinner + locked button while a trigger is running. - **Replies** (`/inbox`) — every reply matched to its prospect + play + cadence status by sender address, merged across all sender identities, with a match-status filter (all / matched / no match) to cut newsletter + bounce noise. Expand a reply to answer it in place: write the draft yourself or **generate with the LLM** (founder voice, primed with the inbound message + your prior touches), edit, and send. Replies go out from the identity that received them and thread on both transports — Gmail via In-Reply-To / References, OneShot via the platform's `reply_to_email_id` (SDK 0.22). Sends carry an idempotency key, so a retry after a timeout can't double-send - **Cadences** — table
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4292766939bea526, topic:ai-agent