Xpersona

Crawler Summary

health-trifecta answer-first brief

A CrewAI demo where physician-, dietitian-, trainer-, and writer-style agents run in sequence on RAG-grounded patient notes and produce a structured HTML health advisory report. Health Trifecta Multi-agent $1 crew that simulates a small care team: a primary care physician, a registered dietitian, a certified personal trainer, and an HTML writer. Together they produce a structured health advisory narrative and a final HTML report grounded in a shared patient knowledge file (crew-level RAG). Disclaimer This project is for **informational and educational use only**. It is **not** medical advice Capability contract not published. No trust telemetry is available yet. Last updated 5/21/2026.

Freshness

Last checked 5/21/2026

Best For

health-trifecta 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 OPENCLEW, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGitHubSafety: 66/100

health-trifecta

A CrewAI demo where physician-, dietitian-, trainer-, and writer-style agents run in sequence on RAG-grounded patient notes and produce a structured HTML health advisory report. Health Trifecta Multi-agent $1 crew that simulates a small care team: a primary care physician, a registered dietitian, a certified personal trainer, and an HTML writer. Together they produce a structured health advisory narrative and a final HTML report grounded in a shared patient knowledge file (crew-level RAG). Disclaimer This project is for **informational and educational use only**. It is **not** medical advice

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

May 21, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 5/21/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 21, 2026

Vendor

Agimat Ai

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Unpublished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 5/21/2026.

View Source

Setup snapshot

git clone https://github.com/agimat-ai/health-trifecta.git
  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

Agimat Ai

profilemedium
Observed May 21, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed May 21, 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 OPENCLEW

Extracted files

0

Examples

3

Snippets

0

Languages

python

Executable Examples

bash

pip install uv
cd health-trifecta
uv sync

bash

crewai run

bash

uv run run_crew

Docs & README

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

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

A CrewAI demo where physician-, dietitian-, trainer-, and writer-style agents run in sequence on RAG-grounded patient notes and produce a structured HTML health advisory report. Health Trifecta Multi-agent $1 crew that simulates a small care team: a primary care physician, a registered dietitian, a certified personal trainer, and an HTML writer. Together they produce a structured health advisory narrative and a final HTML report grounded in a shared patient knowledge file (crew-level RAG). Disclaimer This project is for **informational and educational use only**. It is **not** medical advice

Full README

Health Trifecta

Multi-agent CrewAI crew that simulates a small care team: a primary care physician, a registered dietitian, a certified personal trainer, and an HTML writer. Together they produce a structured health advisory narrative and a final HTML report grounded in a shared patient knowledge file (crew-level RAG).

Disclaimer

This project is for informational and educational use only. It is not medical advice, diagnosis, or treatment, and it is not a substitute for a licensed clinician, dietitian, or trainer.

Outputs are AI-generated and may be incomplete, outdated, or incorrect (including “hallucinations”). The sample patient file is illustrative; do not use this tool for real patient decisions without human professional oversight and appropriate safeguards (including privacy and consent).

What it does

  1. Diagnosis and plan — The primary care physician task uses patient context from the knowledge base to draft a diagnosis and treatment-style plan.
  2. Nutrition — The dietitian reviews that plan and adds evidence-based nutrition guidance, including a weekly Kosher-oriented nutrition plan.
  3. Exercise — The trainer reviews the same clinical plan and adds a weekly exercise plan.
  4. Integrated advisory — The physician synthesizes dietitian and trainer outputs into a comprehensive advisory report (including BMI-related framing and current vs target status in tabular form).
  5. HTML deliverable — The HTML writer turns the advisory into a styled HTML document.

Orchestration is sequential (Process.sequential in src/health_trifecta/crew.py). Tasks declare context dependencies in src/health_trifecta/config/tasks.yaml, so downstream steps automatically receive upstream task outputs as input.

Agents and personas

| Agent | Role (summary) | Default LLM | |--------|----------------|-------------| | primary_care_physician | Holistic primary care framing; uses knowledge for patient facts; synthesizes specialist inputs in the advisory step. | openai/gpt-4o-mini | | registered_dietitian | Evidence-based nutrition advice to support the clinical plan. | openai/gpt-4o-mini | | certified_personal_trainer | Evidence-based exercise advice aligned with the clinical plan. | openai/gpt-4o-mini | | html_writer | Produces the final patient-facing HTML report from the advisory content. | anthropic/claude-opus-4-5-20251101 (override in agents.yaml if your API catalog differs) |

Full prompts (role, goal, backstory) live in src/health_trifecta/config/agents.yaml.

Knowledge sources and RAG

  • Source: TextFileKnowledgeSource in src/health_trifecta/crew.py, wired as knowledge_sources on the Crew.
  • Corpus: knowledge/patient-info.txt (example structured vitals and demographics). Paths are resolved relative to CrewAI’s knowledge/ convention from the configured file path in crew.py.
  • Behavior: At run time, CrewAI indexes/embeds that content and retrieves relevant chunks when agents execute tasks (query-based RAG), so the physician step can ground answers in the file instead of inventing patient details.

To change the corpus, edit or replace knowledge/patient-info.txt and keep the TextFileKnowledgeSource file_paths in crew.py consistent with your layout.

Outputs

  • output/health_advisory_report.html — Written by the html_writer_task (tasks.yaml output_file).

Installation

Requires Python >=3.10, <3.14. Dependencies are managed with uv.

pip install uv
cd health-trifecta
uv sync

The project pins crewai[google-genai,tools,anthropic] so OpenAI-, Google-, and Anthropic-routed models used in YAML are installable from one lockfile.

Environment

Create a .env in the project root with at least the keys below:

  • OPENAI_API_KEY — Required for agents on OpenAI models.
  • ANTHROPIC_API_KEY — Required for the HTML writer when using an anthropic/... model.
  • MODEL (optional) — Default model hint for tooling; agents still follow per-agent llm in agents.yaml.
  • CREWAI_STORAGE_DIR (optional) — Overrides CrewAI app data naming for SQLite and related storage; use a writable directory if you hit database permission errors.

Running

From the repository root:

crewai run

or:

uv run run_crew

Customizing

  • src/health_trifecta/config/agents.yaml — Roles, goals, backstories, and llm strings per agent.
  • src/health_trifecta/config/tasks.yaml — Task descriptions, context lists, expected_output, and output_file.
  • src/health_trifecta/crew.py — Crew process, verbosity, and knowledge source definitions.
  • src/health_trifecta/main.py — Kickoff inputs and CLI entrypoints (run, train, replay, test).

Support

Contract & API

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

MissingGITHUB OPENCLEW

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-agimat-ai-health-trifecta/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/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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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-agimat-ai-health-trifecta/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T01:08:35.339Z"
    }
  },
  "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",
    "label": "Vendor",
    "value": "Agimat Ai",
    "category": "vendor",
    "href": "https://github.com/agimat-ai/health-trifecta",
    "sourceUrl": "https://github.com/agimat-ai/health-trifecta",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-21T06:56:48.826Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-21T06:56:48.826Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "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,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-agimat-ai-health-trifecta/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

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,
    "metadata": {}
  }
]

Sponsored

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