paperzilla
Chat with your agent about projects, recommendations, and canonical papers in Paperzilla. Use when users ask for recent project recommendations, canonical paper details, markdown-based summaries, recommendation feedback, feed export, or Atom feed URLs.
خود اسکیل
# Paperzilla Use this skill when you want to chat with your agent about projects, recommendations, and canonical papers in Paperzilla. ## What you can ask - "Give me the latest recommendations from project X." - "Open recommendation Y and explain why it matters." - "Fetch canonical paper Z as markdown and summarize it." - "Tell me how this paper is relevant to my research." - "Show me the feed for project X." - "Leave feedback on a recommendation." - "Export this paper, recommendation, or feed as JSON." This is the core Paperzilla skill. It gives your agent direct access to Paperzilla data, but it does not impose a workflow or external delivery integration. ## Access method Most current profiles in this repo use the `pz` CLI. If the current profile ships extra agent-specific instructions, follow those as well. ## Install ### macOS ```bash brew install paperzilla-ai/tap/pz ``` ### Windows (Scoop) ```bash scoop bucket add paperzilla-ai https://github.com/paperzilla-ai/scoop-bucket scoop install pz ``` ### Linux Use the official Linux install guide: - https://docs.paperzilla.ai/guides/cli-getting-started ### Build from source (Go 1.23+) See the CLI repository for source builds: - https://github.com/paperzilla-ai/pz ## Update Check whether your CLI is up to date and get install-specific upgrade steps: ```bash pz update ``` If detection is ambiguous, override it explicitly: ```bash pz update --install-method homebrew pz update --install-method scoop pz update --install-method release pz update --install-method source ``` Supported values are `auto`, `homebrew`, `scoop`, `release`, and `source`. ## Authentication ```bash pz login ``` ## CLI reference If the current profile uses `pz`, these are the core commands. ### List projects ```bash pz project list ``` ### Show one project ```bash pz project <project-id> ``` ### Browse project feed ```bash pz feed <project-id> ``` Useful flags: - `--must-read` - `--since YYYY-MM-DD` - `--limit N` - `--json` - `--atom` Examples: ```bash pz feed <project-id> --must-read --since 2026-03-01 --limit 5 pz feed <project-id> --json pz feed <project-id> --atom ``` Feed output can include existing recommendation feedback markers: - `[↑]` upvote - `[↓]` downvote - `[★]` star ### Read a canonical paper ```bash pz paper <paper-id> pz paper <paper-id> --json pz paper <paper-id> --markdown pz paper <paper-id> --project <project-id> ``` ### Open a recommendation from one of your projects ```bash pz rec <project-paper-id> pz rec <project-paper-id> --json pz rec <project-paper-id> --markdown ``` ### Leave recommendation feedback ```bash pz feedback <project-paper-id> upvote pz feedback <project-paper-id> star pz feedback <project-paper-id> downvote --reason not_relevant pz feedback clear <project-paper-id> ``` ## Output and automation - Prefer `--json` for machine parsing. - `pz paper --markdown` only returns markdown when it is already prepared. - `pz rec --markdown` can queue markdown generation and prints a friendly retry message while it is still being prepared. - `--atom` returns a personal feed URL for feed readers. ## Configuration ```bash export PZ_API_URL="https://paperzilla.ai" ``` ## References - Docs: https://docs.paperzilla.ai/guides/cli - Quickstart: https://docs.paperzilla.ai/guides/cli-getting-started - Repo: https://github.com/paperzilla-ai/pz
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Claude Code / Claude Desktop 1. Create a folder named after the skill inside your skills directory: - Claude Code: `~/.claude/skills/<skill-name>/` - A project-local skill: `<project>/.claude/skills/<skill-name>/` 2. Save the text below as `SKILL.md` in that folder, keeping the `---` frontmatter block at the top — the `name` and `description` fields are what make the skill discoverable. 3. Restart Claude Code, or run `/skills` to confirm it is listed. The skill loads only when its `description` matches what you are doing, so a precise description matters more than a long body.
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