Opendot: A terminal AI agent that snapshots every action so you can undo it
Opendot is an interactive terminal AI agent that snapshots every file and shell action, allowing users to undo changes reliably. It is model‑agnostic, supporting any LLM through LiteLLM and offering a local option via Ollama. The tool also integrates with MCP servers and Composio services for extended functionality while flagging potentially irreversible commands for confirmation.
- ▪Every action taken by opendot is snapshotted, enabling users to view and revert changes with commands like opendot undo.
- ▪The agent works with any language model via LiteLLM and can run locally using Ollama without requiring an API key.
- ▪Commands that could affect the system outside the workspace, such as network calls or sudo operations, are flagged and require user confirmation before execution.
- ▪Opendot can connect to external MCP servers and Composio’s suite of 1000+ apps, expanding its capabilities beyond built‑in file and shell actions.
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,813 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/vedaant00/opendot |
| Publication time | Wed, 29 Jul 2026 18:11:00 +0000 |
| Retrieval time | 2026-07-29T18:21:30.023Z |
| Last seen | 2026-07-29T18:21:30.023Z |
| 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 | cCBM9o4bMQJg · 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
An interactive terminal AI agent you can fully undo. opendot works directly on your real files and shell — but unlike other terminal agents, every action it takes is snapshotted first, so you can see exactly what it did and cleanly walk it back. Files and shell commands, not just in-repo edits. Commands whose effects escape your workspace (network, sudo, git push, deleting outside the working dir) are flagged and confirmed before they run, with an honest note about what can't be undone. That's the point of opendot: an agent you can let loose because nothing it does is a surprise, and (almost) nothing is irreversible. opendot is model-agnostic — it works with any model through LiteLLM (OpenAI, Anthropic, Google, DeepSeek, …) and runs fully local via Ollama.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.