I built a personal AI agent in Swift on top of what macOS ships
One pure-Swift daemon on hardware you own. clawd pairs a private Telegram bot with the LLM of your choice. It remembers what you tell it and runs scheduled and proactive tasks. Consequential tool calls wait for your approval.
- ▪One pure-Swift daemon on hardware you own. clawd pairs a private Telegram bot with the LLM of your choice.
- ▪It remembers what you tell it and runs scheduled and proactive tasks.
- ▪Consequential tool calls wait for your approval.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,592 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/ivan-magda/swift-claw |
| Publication time | Wed, 12 Aug 2026 12:23:50 +0000 |
| Retrieval time | 2026-08-12T12:26:30.528Z |
| Last seen | 2026-08-12T12:26:30.528Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | jyxRFnZjzIcN · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Your always-on personal AI assistant. One pure-Swift daemon on hardware you own. clawd pairs a private Telegram bot with the LLM of your choice. It remembers what you tell it and runs scheduled and proactive tasks. Consequential tool calls wait for your approval. Everything it keeps stays in one directory on your own machine: a SQLite database, encrypted secret envelopes, and Markdown files you edit by hand. Features A real Telegram chat. Answers stream in as live message drafts. /stop cancels a turn, /new starts a fresh session, clawd transcribes voice notes on-device (macOS 26), and it looks at photos you send if your model can see them. Durable memory. Facts you confirm persist in SQLite, and clawd recalls them by importance and recency.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.