8.2
/ 10
1 evaluations
4.2k Downloads
Overview
Provide a CLI/agent interface to Beeper Desktop’s local API so an AI agent can list, search, and manage chats/messages/contacts/reminders, and perform limited mutations (send/edit messages, reactions, reminders, file sends) with structured JSON results.
Key Advantages
1.Deep, well-documented coverage of Beeper Desktop features: accounts, contacts, chats, messages, reactions, assets, reminders, unread rollups, and status.
2.Explicit agent-oriented mode (`rr --agent`) that enforces JSON, envelopes, and no-input defaults, making it suitable for automated tool use.
3.Strong safety affordances: read-only by default, explicit opt-in for write commands, `--dry-run`, `--readonly`, `--enable-commands`, and structured envelope errors for controlled retries.
4.Local execution against Beeper Desktop’s API, which avoids transmitting account tokens or raw data externally and keeps message history on-device.
5.Rich search and pagination support (`--all`, `--max-items`, cursor-based paging, JSONL) enables scalable operations on large chat histories with good control over volume limits and resource usage.
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Use Cases
- Let an agent search and summarize Beeper chats or messages about a topic (e.g., "find all messages about the deploy from last week and summarize decisions").
- Provide unread rollups and status dashboards across messaging accounts (e.g., "show my unread important chats and their last message").
- Assist with contact and chat resolution workflows (search contacts, resolve ambiguous names, start DMs based on emails or full names).
- Draft or prepare messages and reminders (including `focus` drafts and `reminders set`) when the user explicitly asks, with the option to dry-run before sending.
- Download or reference attachments from relevant messages (e.g., locating and saving recent shared files from a project chat).
Evaluation Scores
8.2
/ 10
Reliability
8.0
Functionality
9.0
Usability
8.2
Safety
7.8
Performance
8.5
Compatibility
7.5
Based on 1 evaluation · Latest: 3/19/2026
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Evaluation History (1)
8.2/103/19/2026▼
OS: darwin-x64LLM: anthropic/claude-opus-4.6
**Judgement:** Roadrunner is a strong, feature-rich skill for automating and querying Beeper Desktop via its local CLI. It’s well-suited for power users who explicitly want an agent to interact with their real chats and messages, but it carries inherent side-effect risks and requires correct local setup.
**What it’s good for**
- High-fidelity access to Beeper data: listing/searching chats and messages, unread rollups, status, and global search.
- Operational workflows: monitoring chats (tail/wait), summarizing conversations, locating attachments, and managing reminders.
- Agent-safe integration: `--agent`, `--json`, `--envelope`, `--readonly`, `--enable-commands`, and pagination controls give the agent precise, structured, and bounded access.
**Key risks / limitations**
- **Side-effectful operations:** The skill can send/edit messages, create/archive chats, set reminders, and upload/send files. Misinterpretation of user intent or ambiguous chat IDs could lead to unintended messages or chat state changes.
- **Privacy and data exposure:** While output is local, the agent sees real message content. Summaries or answers must avoid dumping raw JSON or unnecessary sensitive details.
- **Environment coupling:** Requires Beeper Desktop running, valid auth, and `rr` installed; unusable outside that environment. Some features (e.g., websocket events) are experimental and may fail or require fallbacks.
**Recommended scenarios**
- Users who explicitly say they want to control Beeper Desktop or Beeper chats via CLI/automation.
- Agents that help triage large volumes of messages (search, filter, summarize) or monitor for specific keywords/events.
- Workflow automation where read-only queries are primary, with occasional, clearly requested mutations (e.g., “send this exact message to chat X”, “set a 2h reminder on this thread”).
**Use with extra caution when**
- The user’s request is vague about recipients or exact message content (the agent should clarify before any mutation).
- The user is not clearly aware that the agent is operating on **real** chats; in such cases prefer read-only operations or confirm explicitly before writing.
- Handling especially sensitive conversations, where even summarized exposure to the agent may be undesirable.
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