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pubmed-paper-monitor
by
Chenghan66
· GitHub ↗
· v1.0.0
· MIT-0
75
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install pubmed-paper-monitor
Description
Monitor journals precisely via ISSN lookup to track new PubMed papers with bilingual titles and detailed metadata.
Usage Guidance
This skill appears to implement a PubMed ISSN-based monitor but has several red flags you should consider before installing: (1) the code hardcodes a third‑party email address (Entrez.email) — you should replace it with your own contact or make it configurable; (2) the SKILL.md install line is malformed and may not install Biopython automatically — ensure Biopython is installed from a trusted source; (3) SKILL.md requires behavior (3 retries, exclusive use of monitor.py) that the script does not implement — expect runtime mismatches; (4) the skill will write full reports to your Desktop when >20 articles — review what data it will store and whether that is acceptable. If you proceed, ask the author to (a) remove or make the Entrez.email configurable, (b) fix the install metadata, and (c) add clear retry/failure behavior or allow fallback sources so the instructions and code match. If you cannot validate those fixes, treat the skill as untrusted or run it in an isolated environment.
Capability Assessment
Purpose & Capability
The code (monitor.py) and SKILL.md align with the stated purpose: searching NCBI/Entrez for journals and PubMed articles via ISSN or journal name. The script imports Biopython (Bio.Entrez), which is a reasonable dependency for this purpose. However the SKILL.md metadata contains a malformed install line ('uv pip install biopython') instead of a clear install step, and the script hardcodes Entrez.email to a third-party personal email rather than allowing the user to supply their own contact address — this is unexpected and should have been declared as a configurable parameter.
Instruction Scope
SKILL.md mandates strict behavior: use monitor.py only, avoid Crossref/internal search unless 'monitor.py fails after 3 retries', and require immediate bilingual translation plus saving full reports to the Desktop if >20 articles. The monitor.py implementation contains no retry logic or failure-count reporting, so the '3 retries' rule cannot be satisfied by the script as provided — this is an inconsistency. The requirement that the agent perform translations itself (rather than calling a translation API) is a functional constraint but not inherently dangerous; however the instructions force writing potentially large, unencrypted data to the user's Desktop which may have privacy implications.
Install Mechanism
There is no formal install spec in the package; the skill is instruction-only plus a Python script. The SKILL.md metadata suggests installing Biopython (which the script needs) but the entry is malformed ('uv pip install biopython') and therefore unreliable as an automated install instruction. Because the dependency is a normal PyPI package and there are no downloads from unknown URLs, install risk is low if the dependency is installed from a trusted source — but the metadata mismatch is sloppy and could break deployment.
Credentials
The skill requests no environment variables or credentials, which is appropriate. However the code hardcodes Entrez.email to '[email protected]' — this is a privacy/attribution concern (network requests will be attributed to that email at NCBI) and is unexpected for a user-facing skill. The skill does not provide a documented way for the user to supply their own email/contact or to configure API rate/settings; that reduces proportionality and control for the end user.
Persistence & Privilege
The skill does not request persistent privileges (always:false) and does not modify other skills or system config. It can be invoked autonomously by the agent (disable-model-invocation:false) which is the platform default — this alone is not a new risk given the other concerns, but note the skill's instructions mandate automatic writing of reports to the Desktop which increases its potential to persist user data.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install pubmed-paper-monitor - After installation, invoke the skill by name or use
/pubmed-paper-monitor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
pubmed-paper-monitor 1.0.0
- Initial release of precision journal monitor using ISSN lookup for high accuracy.
- Only monitor.py script is to be used for lookups; fallback to other sources allowed after multiple failures.
- Automatically translates every article title to professional Chinese; user does not need to call other translation tools.
- If over 20 articles are found, notifies user and saves a detailed bilingual report to Desktop with required data fields.
- Strict output template enforced for all entries, ensuring clarity and consistency.
Metadata
Frequently Asked Questions
What is pubmed-paper-monitor?
Monitor journals precisely via ISSN lookup to track new PubMed papers with bilingual titles and detailed metadata. It is an AI Agent Skill for Claude Code / OpenClaw, with 75 downloads so far.
How do I install pubmed-paper-monitor?
Run "/install pubmed-paper-monitor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is pubmed-paper-monitor free?
Yes, pubmed-paper-monitor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does pubmed-paper-monitor support?
pubmed-paper-monitor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created pubmed-paper-monitor?
It is built and maintained by Chenghan66 (@chenghan66); the current version is v1.0.0.
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