recally

name	recally
description	Reading assistant for saving, organizing, and recalling web content. Use when the user says "save this article", "read this link", "summarize this", "check my feeds", "add to my library", or asks about previously saved content. Handles articles, tweets, YouTube videos, GitHub repos, PDFs, and RSS feeds. Articles are stored as markdown files with metadata and indexed for fast search.
metadata	{"author":"CherryHQ/stella","owner_plugin":"system/recally","version":"1.0"}

Recally - Reading Assistant

Environment: The CLI talks HTTP to the running stella server. STELLA_TOKEN is auto-set; the agent process inherits a reachable STELLA_SERVER_URL (default http://127.0.0.1:25678). Do not pass user identity flags. Do not try to open the SQLite database directly.

References

Topic	File
Saving an article (fetch → generate → save)	references/save-workflow.md
RSS batch processing	references/rss-workflow.md

Search and Retrieve

stella recally search "query" --limit 20 --json
stella recally list --status unread --starred --source-type web --limit 20 --json
stella recally read <id>

list filters: --status (unread/read/archived), --source-type (web/twitter/youtube/github/rss/pdf), --starred, --limit.

Workflow: search → read for details. Never assume content without reading.

Manage Articles

stella recally update <id> --status read --starred
stella recally update <id> --tags "tag1" --tags "tag2"   # replaces existing tags
stella recally update <id> --summary "..."
stella recally delete <id>

RSS Feeds

stella recally feed add <feed-url>
stella recally feed poll --limit 20 --json     # returns pending entries
stella recally feed list
stella recally feed remove <feed-id>

For processing pending entries, see references/rss-workflow.md.

Daily Digest

stella recally digest

Format for user:

Reading Digest for [Date]
📚 Yesterday's saves ([count]): [title] - [summary], ...
📖 Your library: [total] articles ([unread] unread, [read] read, [starred] ⭐)
🔔 Worth revisiting: [count] unread articles 3+ days old
🏷️ Trending tags: tag1 (N), tag2 (N), ...

Limitations

• Search: metadata-only (title, summary, tags, author). Full-body search requires read.
• Deduplication: canonical URL; mobile/desktop variants may duplicate.