How should FoodCatalyst be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Claim this agent

Agent DossierGITHUB REPOSSafety 66/100

Xpersona Agent

FoodCatalyst

Research trending and highly-rated restaurants in your area. with crewai and gemini llm FoodCatalyst Crew $1 $1 Welcome to FoodCatalyst Crew, an AI-powered restaurant discovery and planning system built with $1. This project uses multiple AI agents working together to research, analyze, and create personalized dining itineraries based on your preferences. 🍽️ Project Overview StoryCatalyst transforms how you discover and plan dining experiences by leveraging specialized AI agents that: 1. Research trend

OpenClaw · self-declared

1 GitHub starsTrust evidence available

View Source

Overall rank

#20

Adoption

1 GitHub stars

Trust

Unknown

Freshness

Feb 25, 2026

Freshness

Last checked Feb 25, 2026

Best For

FoodCatalyst 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

Overview Evidence & Timeline Artifacts & Docs API & Reliability Media & Related Machine Appendix

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

No verified compatibility signals1 GitHub stars

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 25, 2026

Vendor

Akshaykarthicks

Artifacts

Benchmarks

Last release

Unpublished

Install & run

Setup Snapshot

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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 & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Akshaykarthicks

profilemedium

Observed Apr 15, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Apr 15, 2026Source link Provenance

Adoption (1)

Adoption signal

1 GitHub stars

profilemedium

Observed Apr 15, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Events

Release & Crawl Timeline

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 & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredGITHUB REPOS

Captured outputs

Artifacts Archive

Extracted files

Examples

Snippets

Languages

python

Executable Examples

mermaid

graph TD
    A[User Input: Preferences & Location] --> B[Scout Agent: Research Restaurants]
    B --> C[Restaurant List with Details]
    C --> D[Critic Agent: Analyze Restaurants]
    D --> E[Restaurant Analysis with Ratings]
    E --> F[Planner Agent: Create Itinerary]
    F --> G[Personalized Dining Plan]
    G --> H[Final Report in Markdown]

bash

pip install uv

bash

crewai install

env

OPENAI_API_KEY=your_openai_api_key_here
SERPER_API_KEY=your_serper_api_key_here

bash

crewai run

python

inputs = {
    'topic': 'Italian cuisine',        # Type of cuisine or dining preference
    'location': 'New York',            # City or area for restaurant search
    'current_year': str(datetime.now().year)
}

Editorial read

Docs & README

Docs source

GITHUB REPOS

Editorial quality

ready

Full README

FoodCatalyst Crew

Welcome to FoodCatalyst Crew, an AI-powered restaurant discovery and planning system built with crewAI. This project uses multiple AI agents working together to research, analyze, and create personalized dining itineraries based on your preferences.

🍽️ Project Overview

StoryCatalyst transforms how you discover and plan dining experiences by leveraging specialized AI agents that:

Research trending and highly-rated restaurants in your area
Analyze restaurant details to provide comprehensive insights
Create personalized dining itineraries based on your preferences

Whether you're a local looking for new dining experiences or a traveler seeking the best local cuisine, StoryCatalyst creates tailored restaurant recommendations that match your taste.

🤖 Agents

Our system consists of three specialized AI agents working in sequence:

Scout (Web-Savvy Restaurant Finder)
- Discovers highly-rated and trending restaurants in your area
- Gathers key details like ratings, cuisine type, and location highlights
Critic (Food Review Analyst)
- Analyzes restaurant reviews, menus, and customer feedback
- Provides balanced assessments highlighting strengths and weaknesses
Planner (Dining Itinerary Builder)
- Creates personalized dining plans based on research and analysis
- Organizes recommendations into a clear, enjoyable dining experience

📋 Workflow

graph TD
    A[User Input: Preferences & Location] --> B[Scout Agent: Research Restaurants]
    B --> C[Restaurant List with Details]
    C --> D[Critic Agent: Analyze Restaurants]
    D --> E[Restaurant Analysis with Ratings]
    E --> F[Planner Agent: Create Itinerary]
    F --> G[Personalized Dining Plan]
    G --> H[Final Report in Markdown]

🚀 Installation

Ensure you have Python >=3.10 <3.14 installed on your system. This project uses UV for dependency management.

First, if you haven't already, install uv:

pip install uv

Next, navigate to your project directory and install the dependencies:

crewai install

Environment Setup

Create a .env file in the project root with your API keys:

OPENAI_API_KEY=your_openai_api_key_here
SERPER_API_KEY=your_serper_api_key_here

▶️ Running the Project

To run the StoryCatalyst Crew:

crewai run

This will execute the agents in sequence and generate a report.md file with your personalized dining itinerary.

Customizing Inputs

Modify the inputs in src/story_catalyst/main.py to customize your search:

inputs = {
    'topic': 'Italian cuisine',        # Type of cuisine or dining preference
    'location': 'New York',            # City or area for restaurant search
    'current_year': str(datetime.now().year)
}

📁 Project Structure

story_catalyst/
├── src/
│   └── story_catalyst/
│       ├── config/
│       │   ├── agents.yaml         # Agent definitions
│       │   └── tasks.yaml          # Task definitions
│       ├── tools/
│       │   ├── custom_tool.py      # Custom tools (if any)
│       │   └── html_generator.py   # HTML report generator tool
│       ├── crew.py                 # Main crew definition
│       └── main.py                 # Entry point
├── knowledge/
│   └── user_preference.txt         # User preference data
├── report.md                       # Generated output (after run)
├── report.html                     # HTML generated output (after run)
├── .env                            # API keys (not in version control)
├── pyproject.toml                  # Project dependencies
└── README.md

⚙️ Configuration

Agents

Modify src/story_catalyst/config/agents.yaml to customize agent roles, goals, and backstories.

Tasks

Modify src/story_catalyst/config/tasks.yaml to adjust task descriptions and expected outputs.

Custom Tools

Add custom tools in src/story_catalyst/tools/ and register them in your agents.

The project includes a custom HTML generator tool (html_generator.py) that creates visually appealing HTML reports from the JSON output of the planning agent.

🛠️ Customization

To customize the StoryCatalyst Crew for your specific needs:

Modify agent configurations in src/story_catalyst/config/agents.yaml
Adjust task parameters in src/story_catalyst/config/tasks.yaml
Add custom logic in src/story_catalyst/crew.py
Change input parameters in src/story_catalyst/main.py

📊 Output

After running, the crew generates two files:

report.md - A markdown report containing:
- A list of recommended restaurants with key details
- Analysis of each restaurant with pros and cons
- A personalized dining itinerary with scheduling suggestions
report.html - An HTML report with the same information in a visually appealing format with styling

🤝 Support

For support, questions, or feedback regarding StoryCatalyst or crewAI:

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Let's create amazing dining experiences together with the power of AI agents!

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Machine interfaces

Contract & API

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

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://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/snapshot"

curl -s "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/contract"

curl -s "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/trust"

Operational fit

Reliability & Benchmarks

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.

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingGITHUB REPOS

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://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-04-17T02:38:34.173Z"
    }
  },
  "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": "Akshaykarthicks",
    "href": "https://github.com/akshaykarthicks/FoodCatalyst",
    "sourceUrl": "https://github.com/akshaykarthicks/FoodCatalyst",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "1 GitHub stars",
    "href": "https://github.com/akshaykarthicks/FoodCatalyst",
    "sourceUrl": "https://github.com/akshaykarthicks/FoodCatalyst",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "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://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-akshaykarthicks-foodcatalyst/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
  }
]

Overview

Executive Summary

Setup Snapshot

Evidence & Timeline

Evidence Ledger

Release & Crawl Timeline

Artifacts & Docs

Artifacts Archive

Docs & README

FoodCatalyst Crew

🍽️ Project Overview

🤖 Agents

📋 Workflow

🚀 Installation

Environment Setup

▶️ Running the Project

Customizing Inputs

📁 Project Structure

⚙️ Configuration

Agents

Tasks

Custom Tools

🛠️ Customization

📊 Output

🤝 Support

📄 License

API & Reliability

Contract & API

Reliability & Benchmarks

Media & Related

Media & Demo

Related Agents

Machine Appendix