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Install in OpenClaw
/install smart-journal-monitor
Description
Use smart journal monitor for evidence insight workflows that need structured execution, explicit assumptions, and clear output boundaries.
Usage Guidance
This skill is internally inconsistent: it advertises 'RSS+AI' monitoring but the shipped script only scores local JSON articles and makes no network or model calls. Before installing or using it: 1) ask the author to explain where RSS ingestion and AI processing are implemented (or provide the missing code/config); 2) review the script yourself (or have someone you trust do so) and confirm it matches your expectations; 3) if you plan to run it, test using the demo flag and sample JSON in a sandboxed environment and avoid supplying sensitive data in the --articles file; 4) consider asking for version-pinned dependencies and a clear CONFIG or README that documents real inputs/outputs. The mismatch may be benign (unfinished or placeholder skill) but do not assume it provides the advertised RSS/AI capabilities without further clarification.
Capability Analysis
Type: OpenClaw Skill
Name: smart-journal-monitor
Version: 1.0.0
The skill bundle provides a simple Python script (scripts/main.py) for scoring and filtering research articles based on journal impact and keywords. The code is straightforward, contains no network or sensitive file system access, and lacks any signs of obfuscation or malicious intent. The instructions in SKILL.md are consistent with the stated purpose of providing a structured workflow for journal monitoring.
Capability Assessment
Purpose & Capability
The name/description advertise 'RSS+AI' and "monitoring" of journals, but the only executable (scripts/main.py) performs a simple, local scoring of articles loaded from a provided JSON file or demo data. There is no RSS retrieval, no network or API calls, and no AI/model usage in the code. The SKILL.md also mentions a CONFIG block and packaged behavior not present in the script. The requested capabilities (RSS ingestion, AI analysis) are not implemented, so the declared purpose and actual capability are inconsistent.
Instruction Scope
SKILL.md instructs the agent to validate inputs and run the packaged script (python -m py_compile and python scripts/main.py --help), which matches the code's CLI. However, the documentation references additional artifacts (a CONFIG block, packaged RSS/AI workflows, and 'references/' guidance) that are not implemented or are only minimal. The instructions do not ask for unrelated system files or credentials, and the runtime behavior described (no external API calls) matches the code.
Install Mechanism
There is no install specification — this is instruction-only with a small included Python script. That is low-risk from an installation perspective; nothing is downloaded or installed by the skill itself.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The script operates on local JSON input passed via --articles, so no extra environment or secrets are requested — this is proportionate to the implemented functionality.
Persistence & Privilege
always is false and the skill does not request persistent presence or modify agent/system configuration. It only contains a CLI script intended for on-demand invocation.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install smart-journal-monitor - After installation, invoke the skill by name or use
/smart-journal-monitor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
smart-journal-monitor 1.0.0 – Initial release
- Provides a structured evidence insight workflow for monitoring research journals using clear assumptions, explicit input validation, and reproducible output.
- Main execution via scripts/main.py with workflow guidance, usage examples, and audit-ready validation steps.
- Returns curated article lists with impact scores, relevance ranking, and concise summaries.
- Includes transparent error handling, security checklist, and documented fallback procedures for missing inputs or execution errors.
- No external dependencies or network access required; all processing and outputs remain local to the workspace.
Metadata
Frequently Asked Questions
What is Smart Journal Monitor(RSS+AI)?
Use smart journal monitor for evidence insight workflows that need structured execution, explicit assumptions, and clear output boundaries. It is an AI Agent Skill for Claude Code / OpenClaw, with 88 downloads so far.
How do I install Smart Journal Monitor(RSS+AI)?
Run "/install smart-journal-monitor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Smart Journal Monitor(RSS+AI) free?
Yes, Smart Journal Monitor(RSS+AI) is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Smart Journal Monitor(RSS+AI) support?
Smart Journal Monitor(RSS+AI) is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Smart Journal Monitor(RSS+AI)?
It is built and maintained by AIpoch (@aipoch-ai); the current version is v1.0.0.
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