Xpersona

Crawler Summary

Hospital-Discharge-Planning-Assistant-with-Human-Approval- answer-first brief

AI-powered Hospital Discharge Planning Assistant using CrewAI that combines multi-agent reasoning, knowledge retrieval, and human-in-the-loop approval to generate personalized discharge summaries and care recommendations. Hospital Discharge Planning Multi-Agent System A CrewAI-based multi-agent system that automates hospital discharge planning for diabetic patients. The system uses three specialized AI agents (physician, nurse, and medication specialist) working sequentially with knowledge sources, followed by mandatory human physician review. Overview This project demonstrates a production-ready agentic AI workflow for healthcare wit Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

Hospital-Discharge-Planning-Assistant-with-Human-Approval- is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB REPOS, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Agent DossierGITHUB REPOSSafety: 66/100

Hospital-Discharge-Planning-Assistant-with-Human-Approval-

AI-powered Hospital Discharge Planning Assistant using CrewAI that combines multi-agent reasoning, knowledge retrieval, and human-in-the-loop approval to generate personalized discharge summaries and care recommendations. Hospital Discharge Planning Multi-Agent System A CrewAI-based multi-agent system that automates hospital discharge planning for diabetic patients. The system uses three specialized AI agents (physician, nurse, and medication specialist) working sequentially with knowledge sources, followed by mandatory human physician review. Overview This project demonstrates a production-ready agentic AI workflow for healthcare wit

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Oct 9, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Oct 9, 2026

Vendor

Krithi Lakshmi

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

View Source

Setup snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Krithi Lakshmi

profilemedium
Observed Oct 9, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Oct 9, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

Extracted files

0

Examples

6

Snippets

0

Languages

python

Executable Examples

text

┌─────────────────┐      ┌─────────────────┐      ┌──────────────────┐
│  Doctor Agent   │  →   │  Nurse Agent    │  →   │ Medication Agent │
│  (Clinical      │      │  (Patient       │      │  (Drug Safety)   │
│   Assessment)   │      │   Education)    │      │                  │
└─────────────────┘      └─────────────────┘      └──────────────────┘
        │                        │                          │
        └────────────────────────┴──────────────────────────┘
                                 ↓
                    ┌─────────────────────────┐
                    │   Human Physician       │
                    │   Review (Required)     │
                    └─────────────────────────┘
                                 ↓
                    ┌─────────────────────────┐
                    │   Final Discharge       │
                    │   Summary               │
                    └─────────────────────────┘

bash

git clone https://github.com/yourusername/hospital-discharge-crew.git
cd hospital-discharge-crew

bash

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

bash

pip install -r requirements.txt

bash

cp .env.example .env
# Edit .env and add your OpenAI API key

bash

python generate_pdf.py

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

AI-powered Hospital Discharge Planning Assistant using CrewAI that combines multi-agent reasoning, knowledge retrieval, and human-in-the-loop approval to generate personalized discharge summaries and care recommendations. Hospital Discharge Planning Multi-Agent System A CrewAI-based multi-agent system that automates hospital discharge planning for diabetic patients. The system uses three specialized AI agents (physician, nurse, and medication specialist) working sequentially with knowledge sources, followed by mandatory human physician review. Overview This project demonstrates a production-ready agentic AI workflow for healthcare wit

Full README

Hospital Discharge Planning Multi-Agent System

A CrewAI-based multi-agent system that automates hospital discharge planning for diabetic patients. The system uses three specialized AI agents (physician, nurse, and medication specialist) working sequentially with knowledge sources, followed by mandatory human physician review.

Overview

This project demonstrates a production-ready agentic AI workflow for healthcare with:

  • Multi-agent collaboration through specialized roles
  • Multiple knowledge source types (PDF, CSV, JSON, text)
  • Human-in-the-loop oversight for clinical safety
  • Strict guardrails preventing hallucinated medical information
  • Sequential workflow with clear handoffs

Architecture

┌─────────────────┐      ┌─────────────────┐      ┌──────────────────┐
│  Doctor Agent   │  →   │  Nurse Agent    │  →   │ Medication Agent │
│  (Clinical      │      │  (Patient       │      │  (Drug Safety)   │
│   Assessment)   │      │   Education)    │      │                  │
└─────────────────┘      └─────────────────┘      └──────────────────┘
        │                        │                          │
        └────────────────────────┴──────────────────────────┘
                                 ↓
                    ┌─────────────────────────┐
                    │   Human Physician       │
                    │   Review (Required)     │
                    └─────────────────────────┘
                                 ↓
                    ┌─────────────────────────┐
                    │   Final Discharge       │
                    │   Summary               │
                    └─────────────────────────┘

Agents

1. Senior Discharge Planning Physician

  • Analyzes laboratory results and clinical data
  • Generates evidence-based discharge recommendations
  • Identifies risk factors and follow-up needs
  • Knowledge source: Discharge guidelines PDF

2. Senior Patient Education Nurse

  • Creates patient-friendly discharge instructions
  • Provides dietary, monitoring, and lifestyle guidance
  • Translates clinical recommendations to actionable steps
  • Knowledge source: Nursing instructions text

3. Clinical Medication Specialist

  • Reviews medication safety and dosing
  • Highlights interactions and side effects
  • Flags missing or uncertain medication data
  • Knowledge source: Medications JSON database

Knowledge Sources

| Source | Type | Purpose | |--------|------|---------| | hospital_policy.txt | StringKnowledgeSource | Hospital discharge policies (shared) | | patient_lab_results.csv | CSVKnowledgeSource | Patient lab data (shared) | | medications.json | JSONKnowledgeSource | Medication database | | nursing_instructions.txt | StringKnowledgeSource | Patient education guide | | discharge_guidelines.pdf | PDFKnowledgeSource | Clinical discharge standards |

Setup

Prerequisites

  • Python 3.10 or higher
  • OpenAI API key (or compatible LLM provider)

Installation

  1. Clone the repository:
git clone https://github.com/yourusername/hospital-discharge-crew.git
cd hospital-discharge-crew
  1. Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Configure environment variables:
cp .env.example .env
# Edit .env and add your OpenAI API key
  1. Generate the PDF knowledge source (if not already present):
python generate_pdf.py

Usage

Run the discharge planning workflow:

python main.py

The system will:

  1. Execute the doctor agent's clinical assessment
  2. Execute the nurse agent's patient education
  3. Execute the medication agent's drug review
  4. Pause for human physician review (you'll be prompted)
  5. Generate the final discharge summary

Sample Output

The system produces:

  • Clinical Discharge Assessment Report
  • Nursing Education Report
  • Medication Report
  • Final Approved Discharge Summary (after human review)

Safety Features

  • No hallucination policy: Agents explicitly state when information is unavailable
  • Knowledge boundaries: Each agent only uses authorized knowledge sources
  • Human-in-the-loop: Physician review required before final summary
  • Audit trail: All agent reasoning is logged via verbose mode
  • Conservative defaults: Agents flag uncertainty and high-risk indicators

Disclaimer

This is a demonstration project for educational purposes. It is not intended for actual clinical use. Real clinical decision support systems require:

  • FDA regulatory approval
  • HIPAA-compliant infrastructure
  • Validation against clinical outcomes
  • Integration with certified EHR systems
  • Comprehensive testing and validation
  • Licensed medical professional oversight

License

MIT License - see LICENSE file for details.

Acknowledgments

Built with CrewAI - an open-source framework for orchestrating role-playing AI agents.

Contributing

Contributions welcome. Please open an issue or pull request.

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

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Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-10T06:24:41.245Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Krithi Lakshmi",
    "href": "https://github.com/Krithi-Lakshmi/Hospital-Discharge-Planning-Assistant-with-Human-Approval-",
    "sourceUrl": "https://github.com/Krithi-Lakshmi/Hospital-Discharge-Planning-Assistant-with-Human-Approval-",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T20:05:59.260Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T20:05:59.260Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-krithi-lakshmi-hospital-discharge-planning-assistant-wit/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

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