papr-rss
Read, search and triage the user's Papr RSS subscriptions from the shell via the `papr` CLI. Use when the user wants to catch up on their feeds, find or summarize articles they've subscribed to, check what's unread, star/save articles, subscribe to a new feed, or pull new posts. Triggers on: "what's in my feeds", "any unread RSS", "summarize this feed", "search my subscriptions for X", "mark these read", "subscribe to <url>", "refresh my feeds".
DeepseekModel
Curated skill
Quality Excellent · 90
v1.0.0
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https://deepseekmodel.com/api/download.php?id=l0ng-ai-papr-skills-papr-rss-skill-md&format=skill
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Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name papr-rss description Read, search and triage the user's Papr RSS subscriptions from the shell via the `papr` CLI. Use when the user wants to catch up on their feeds, find or summarize articles they've subscribed to, check what's unread, star/save articles, subscribe to a new feed, or pull new posts. Triggers on: "what's in my feeds", "any unread RSS", "summarize this feed", "search my subscriptions for X", "mark these read", "subscribe to <url>", "refresh my feeds". Papr RSS CLI papr is a token-efficient, agent-facing CLI over the user's local Papr RSS database. It emits TOON on stdout (≈40% cheaper than JSON, via the official toon-format encoder), keeps diagnostics on stderr, and returns structured errors with exit codes (0 success/no-op, 1 runtime, 2 usage). Reads are token-minimal by default; long article bodies are truncated with a --full escape hatch. Run papr with no arguments first — it prints the unread dashboard plus the most useful next commands, so you can orient without reading a manual. Core flow papr # home: unread/starred counts + recent unread + next steps papr feeds # subscriptions grouped by folder, with unread counts papr list --feed < id > # articles in a feed (defaults to unread; --all for read too) papr list --starred # smart views: --starred / --later / --tag <id> / --folder <id> papr list --fields author,url # add columns: author,url,snippet,type,feed_id,published papr read < id > [< id >...] # plain-text body, truncated; pass several ids to batch papr read --feed < id > --unread -- limit 5 # read a feed's latest unread in one call papr read < id > --full # the complete body when truncation hid something papr search "<query>" # FTS5 full-text search across every article Triage & subscriptions papr mark read < id > [< id >...] # state: read|unread|star|unstar|later|unlater (idempotent) papr mark-all --feed < id > # mark a whole view read papr subscribe <url> # auto-discovers the feed, inserts it, fetches it papr refresh [--feed < id >] # fetch new articles over the network (RSS + newsletters) papr extract < id > # fetch & store the cleaned full text of an article Management (mirrors the desktop app) papr tags | papr tag add <tag_id> <article_id> | papr tag create "<name>" papr folders | papr folder create "<name>" | papr feed move < id > --folder < id > papr rules | papr rule create "<name>" "<keywords>" --action star papr highlights [--article < id >] | papr highlight create <article_id> "<quote>" papr newsletters | papr newsletter add --title .. --host .. --user .. --password .. papr opml import <file> | papr opml export papr settings get <key> | papr settings set <key> <value> papr stats Sync papr sync status | papr sync run # reconcile read/starred + subscriptions with FreshRSS/Miniflux There are no summarize/ask/digest/translate commands: you are the language model, so read the text with papr read <id> (or gather candidates with papr search ) and summarize, answer or translate it yourself — no second AI provider is involved. Destructive verbs require --yes ; without it they fail with exit 2 and tell you the exact command to re-run: papr unsubscribe < id > -- yes # delete a feed and its articles papr admin cleanup <days> -- yes # also: admin vacuum / admin reset papr folder delete < id > -- yes # likewise tag/rule/highlight delete, newsletter remove Notes Every command takes --db <path> (or the PAPR_DB env var) if the database is not in the desktop app's default location. Output is data, not prose. Each list states a definitive total ( count: N of M unread ) so you never need to paginate just to learn the size. If the answer is "nothing", the command says so explicitly — a zero is an answer, not a reason to retry with different flags. Prefer the ambient SessionStart hook ( papr setup ) so the unread dashboard is already in context at the start of a conversation; this skill is the lower-overhead alternative that loads only when a feed task comes up.
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The downloaded .skill package contains the following fields.
| Field | Description |
|---|---|
| format | Format tag (skill/v1) |
| skill_id | Unique skill ID |
| name | Skill name |
| version | Version |
| description | Description |
| category | Categories (array) |
| trigger_words | Trigger words |
| tags | Tags |
| source | Source |
| source_url | Source URL (this page) |
| exported_at | Exported at (set per download) |
| system_prompt | System prompt body |
| model_config | Model config: provider / model / temperature / max_tokens / top_p |
| examples | Examples |
| install_guide | Import guide for Coze / Dify / Claude / custom frameworks |
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