Shift Handover Summarizer
v1.0.0Generate structured shift handover summaries from EHR records, highlighting critical events, vital sign changes, and pending tasks for incoming clinical staff.
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byAIpoch@aipoch-ai
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description (generate structured handover summaries from EHR records) matches the included SKILL.md and the bundled Python script: it reads a JSON records file, analyzes events/vitals, and emits a summary. There are no requested external credentials, binaries, or config paths that would be disproportionate for this purpose.
Instruction Scope
SKILL.md instructs running the included script against a provided records file and specifies required parameters (records file, shift start/end). It explicitly states scope boundaries (does not access live hospital systems) and includes safety/error-handling rules. The instructions do not direct the agent to read unrelated system files, search shell history, or contact external endpoints.
Install Mechanism
No install spec and no external downloads are used; the skill is instruction + bundled Python script. requirements.txt lists only 'dataclasses' and 'enum' (both are standard-library or only needed for older Python versions), so nothing suspicious is pulled from external package hosts.
Credentials
The skill declares no required environment variables, credentials, or config paths. The SKILL.md and visible code do not reference environment secrets or external service tokens. This is proportionate for a tool that processes local EHR JSON files.
Persistence & Privilege
The skill is not always-included and does not request elevated or persistent privileges. There is no evidence it modifies other skills or system-wide settings. Autonomous model invocation is allowed by default but not combined with other concerning behaviors.
Assessment
This package appears to be a self-contained local Python tool for summarizing EHR records. Before installing or running it: 1) Review the full scripts/main.py (you already have it) to confirm there are no hidden network calls or subprocess executions (the visible imports are local-only). 2) Run the script in a controlled environment (air-gapped or on de-identified/test data) to confirm behavior and avoid exposing real patient data. 3) Ensure compliance with your local data-protection policies (HIPAA/GDPR) — do not feed identifiable PHI to third-party systems. 4) Validate outputs on synthetic records to confirm thresholds/keywords match your clinical needs and adjust configuration if needed. If you want extra assurance, paste the remaining truncated portion of scripts/main.py for a full line-by-line review to confirm there are no late imports or hidden network behavior.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.