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.
- License 许可
- MIT
- 最近更新
- 2026-11-08
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- paperzilla
- license
- MIT
- metadata
- { "tags": "paper recommendations, research feeds, literature monitoring", "version": "1.0", "category": "literature-review", "maintainer": "Kalaris Labs", "contributor": "Paperzilla Inc" }
- description
- 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.
03 SKILL.md 正文
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
brew install paperzilla-ai/tap/pz
Windows (Scoop)
scoop bucket add paperzilla-ai https://github.com/paperzilla-ai/scoop-bucket
scoop install pz
Linux
Use the official Linux install guide:
Build from source (Go 1.23+)
See the CLI repository for source builds:
Update
Check whether your CLI is up to date and get install-specific upgrade steps:
pz update
If detection is ambiguous, override it explicitly:
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
pz login
CLI reference
If the current profile uses pz, these are the core commands.
List projects
pz project list
Show one project
pz project <project-id>
Browse project feed
pz feed <project-id>
Useful flags:
--must-read--since YYYY-MM-DD--limit N--json--atom
Examples:
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
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
pz rec <project-paper-id>
pz rec <project-paper-id> --json
pz rec <project-paper-id> --markdown
Leave recommendation feedback
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
--jsonfor machine parsing. pz paper --markdownonly returns markdown when it is already prepared.pz rec --markdowncan queue markdown generation and prints a friendly retry message while it is still being prepared.--atomreturns a personal feed URL for feed readers.
Configuration
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
Agent operating procedure
- Check the environment. Confirm the research question, databases, date range and inclusion criteria.
- Pin down the inputs. Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.
- Run a small version first. Run the search on one database with a narrow query and check that the results are relevant.
- Execute the full task using the instructions and references above.
- Validate the result. Every reference is retrieved from a real record with a resolvable identifier; counts and search strings are recorded.
- Report. State what was run (versions, commands, parameters), what was checked, and what is still uncertain.
| If this happens | Do this |
|---|---|
| An API rate-limits or returns errors | Back off and retry, reduce the batch size, or switch database, and report the gap. |
| A function, flag or endpoint in these instructions is missing in the installed version | Check the installed version's own documentation (help(), --help, official docs), adapt, and tell the user. Never invent an API. |
| A required input, identifier or parameter is ambiguous | Ask the user, or state the assumption explicitly before running. |
Integrity rules
- Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.
- Never summarize a paper you have not retrieved; never cite from memory.
- Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.
- Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.
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