Show HN: dbward – Approval workflows for production DBs, built for AI agents
dbward Open-core project — core components are Apache-2.0. Some features and pre-built binaries include code under the dbward Commercial License. Approval workflows and audit logs for your production database.
- ▪dbward Open-core project — core components are Apache-2.0.
- ▪Some features and pre-built binaries include code under the dbward Commercial License.
- ▪Approval workflows and audit logs for your production database.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,445 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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/dbward-dev/dbward |
| Publication time | Tue, 11 Aug 2026 13:26:59 +0000 |
| Retrieval time | 2026-08-11T14:20:42.195Z |
| Last seen | 2026-08-11T14:20:42.195Z |
| 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 | pIgi39DR9HFn · 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
dbward Open-core project — core components are Apache-2.0. Some features and pre-built binaries include code under the dbward Commercial License. See License for details. Approval workflows and audit logs for your production database. Stop accidents before they hit production. Add approval gates, audit trails, and AI agent guardrails to every database operation — with standalone binaries and embedded SQLite. No external control-plane DB required. Highlights 🔐 Approval workflows — multi-step, conditional auto-approve, TOML policy engine 📋 Audit logs — tamper-evident hash chain, 24 event types, SQL redaction 🤖 MCP-native — 12 tools, 6 prompts, elicitation support. AI agents operate safely.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.