Xpersona

Crawler Summary

crewai-code-debugger answer-first brief

A multi-agent CrewAI system that automatically detects and fixes Python code errors using a sequential pipeline of Code Analyzer, Code Corrector, and Manager agents — powered by GPT-4o and CodeInterpreterTool. 🐛 CrewAI Code Debugger <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python&logoColor=white" /> <img src="https://img.shields.io/badge/CrewAI-1.12%2B-orange?style=for-the-badge&logo=robot&logoColor=white" /> <img src="https://img.shields.io/badge/OpenAI-GPT--4o-412991?style=for-the-badge&logo=openai&logoColor=white" /> <img src="https://img.shields.io/badge/Li Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Freshness

Last checked 4/15/2026

Best For

crewai-code-debugger 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
Claim this agent
Agent DossierGITHUB REPOSSafety: 66/100

crewai-code-debugger

A multi-agent CrewAI system that automatically detects and fixes Python code errors using a sequential pipeline of Code Analyzer, Code Corrector, and Manager agents — powered by GPT-4o and CodeInterpreterTool. 🐛 CrewAI Code Debugger <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python&logoColor=white" /> <img src="https://img.shields.io/badge/CrewAI-1.12%2B-orange?style=for-the-badge&logo=robot&logoColor=white" /> <img src="https://img.shields.io/badge/OpenAI-GPT--4o-412991?style=for-the-badge&logo=openai&logoColor=white" /> <img src="https://img.shields.io/badge/Li

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Sanjai S0

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Unpublished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 4/15/2026.

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

Sanjai S0

profilemedium
Observed Apr 15, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 15, 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

mermaid

flowchart TD
    A([🚀 Start]) --> B[📥 Input: Buggy Python Code]
    B --> C{🧠 Manager Agent\nOversees Workflow}

    C --> D[🔍 Code Analyzer Agent\nCodeInterpreterTool]
    D --> E[📋 Analysis Task\nIdentify Syntax & Logic Errors]
    E --> F[📄 Error Report\nList of Issues Found]

    F --> G[🔧 Code Corrector Agent]
    G --> H[✏️ Correction Task\nFix Identified Errors]
    H --> I[✅ Corrected Python Code]

    I --> J([🏁 End: Output Delivered])

    style A fill:#4CAF50,color:#fff
    style J fill:#4CAF50,color:#fff
    style C fill:#FF9800,color:#fff
    style D fill:#2196F3,color:#fff
    style G fill:#9C27B0,color:#fff
    style F fill:#f5f5f5,stroke:#999
    style I fill:#E8F5E9,stroke:#4CAF50

text

crewai-code-debugger/
├── Flow/
│   └── workflow.mmd            # Mermaid workflow diagram source
├── crewai_debugger.ipynb       # Main notebook — agents, tasks, and crew
├── requirements.txt            # Python dependencies
├── .env.example                # Environment variable template
├── .gitignore
├── LICENSE
└── README.md

python

def fibonacci_iterative(n):
if n < 0:
return []
elif n == 1:
return [0]
elif n == 2:
return [0, 1]
fib_sequence = [0, 1]
for i in range(2, n):
next_fib = fib_sequence[-1] + fib_sequence[-2]
fib_sequence.append(next_fib)
return fib_sequence

python

def fibonacci_iterative(n):
    if n < 0:
        return []
    elif n == 1:
        return [0]
    elif n == 2:
        return [0, 1]
    fib_sequence = [0, 1]
    for i in range(2, n):
        next_fib = fib_sequence[-1] + fib_sequence[-2]
        fib_sequence.append(next_fib)
    return fib_sequence

bash

# 1. Clone the repository
git clone https://github.com/SANJAI-s0/crewai-code-debugger.git
cd crewai-code-debugger

# 2. Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Configure environment variables
cp .env.example .env
# Edit .env and add your OPENAI_API_KEY

bash

jupyter notebook crewai_debugger.ipynb

Docs & README

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

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

A multi-agent CrewAI system that automatically detects and fixes Python code errors using a sequential pipeline of Code Analyzer, Code Corrector, and Manager agents — powered by GPT-4o and CodeInterpreterTool. 🐛 CrewAI Code Debugger <p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python&logoColor=white" /> <img src="https://img.shields.io/badge/CrewAI-1.12%2B-orange?style=for-the-badge&logo=robot&logoColor=white" /> <img src="https://img.shields.io/badge/OpenAI-GPT--4o-412991?style=for-the-badge&logo=openai&logoColor=white" /> <img src="https://img.shields.io/badge/Li

Full README

🐛 CrewAI Code Debugger

<p align="center"> <img src="https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python&logoColor=white" /> <img src="https://img.shields.io/badge/CrewAI-1.12%2B-orange?style=for-the-badge&logo=robot&logoColor=white" /> <img src="https://img.shields.io/badge/OpenAI-GPT--4o-412991?style=for-the-badge&logo=openai&logoColor=white" /> <img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" /> <img src="https://img.shields.io/badge/Process-Sequential-purple?style=for-the-badge" /> <img src="https://img.shields.io/badge/Planning-Enabled-red?style=for-the-badge" /> </p>

A multi-agent system built with CrewAI that automatically detects and fixes errors in Python code. Two specialized agents — a Code Analyzer and a Code Corrector — work sequentially under a Manager agent to deliver clean, corrected code.

📚 Table of Contents

🧠 Overview

This project demonstrates a sequential CrewAI pipeline with planning enabled. Given a snippet of buggy Python code, the system:

  1. Runs the code through a Code Analyzer agent (powered by CodeInterpreterTool) to detect all syntax and logical errors.
  2. Passes the error report to a Code Corrector agent that returns a fully fixed, PEP-8 compliant version.
  3. A Manager agent oversees the entire workflow, coordinating delegation and ensuring quality output.

🔀 Workflow Diagram

flowchart TD
    A([🚀 Start]) --> B[📥 Input: Buggy Python Code]
    B --> C{🧠 Manager Agent\nOversees Workflow}

    C --> D[🔍 Code Analyzer Agent\nCodeInterpreterTool]
    D --> E[📋 Analysis Task\nIdentify Syntax & Logic Errors]
    E --> F[📄 Error Report\nList of Issues Found]

    F --> G[🔧 Code Corrector Agent]
    G --> H[✏️ Correction Task\nFix Identified Errors]
    H --> I[✅ Corrected Python Code]

    I --> J([🏁 End: Output Delivered])

    style A fill:#4CAF50,color:#fff
    style J fill:#4CAF50,color:#fff
    style C fill:#FF9800,color:#fff
    style D fill:#2196F3,color:#fff
    style G fill:#9C27B0,color:#fff
    style F fill:#f5f5f5,stroke:#999
    style I fill:#E8F5E9,stroke:#4CAF50

The .mmd source file is located at Flow/workflow.mmd.

📁 Project Structure

crewai-code-debugger/
├── Flow/
│   └── workflow.mmd            # Mermaid workflow diagram source
├── crewai_debugger.ipynb       # Main notebook — agents, tasks, and crew
├── requirements.txt            # Python dependencies
├── .env.example                # Environment variable template
├── .gitignore
├── LICENSE
└── README.md

🤖 Agents

| Agent | Role | Tool | Delegation | |---|---|---|---| | Code Analyzer | Identifies syntax & logical errors | CodeInterpreterTool | ❌ | | Code Corrector | Fixes all identified errors | — | ❌ | | Manager | Oversees and coordinates the pipeline | — | ✅ |

📋 Tasks

1. Analysis Task

  • Agent: Code Analyzer
  • Tool: CodeInterpreterTool — executes the code inside a Docker container to surface runtime and syntax errors
  • Output: A numbered list of all errors with type, location, and description

2. Correction Task

  • Agent: Code Corrector
  • Context: Receives the error list from the Analysis Task via context=[analysis_task]
  • Output: Complete, corrected Python code ready to run

💡 Example

Input (Buggy Code)

def fibonacci_iterative(n):
if n < 0:
return []
elif n == 1:
return [0]
elif n == 2:
return [0, 1]
fib_sequence = [0, 1]
for i in range(2, n):
next_fib = fib_sequence[-1] + fib_sequence[-2]
fib_sequence.append(next_fib)
return fib_sequence

Expected Output (Corrected Code)

def fibonacci_iterative(n):
    if n < 0:
        return []
    elif n == 1:
        return [0]
    elif n == 2:
        return [0, 1]
    fib_sequence = [0, 1]
    for i in range(2, n):
        next_fib = fib_sequence[-1] + fib_sequence[-2]
        fib_sequence.append(next_fib)
    return fib_sequence

⚙️ Setup & Installation

Prerequisites

  • Python 3.10+
  • Docker Desktop (required by CodeInterpreterTool to execute code safely)
  • An OpenAI API key with an active billing plan

Steps

# 1. Clone the repository
git clone https://github.com/SANJAI-s0/crewai-code-debugger.git
cd crewai-code-debugger

# 2. Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Configure environment variables
cp .env.example .env
# Edit .env and add your OPENAI_API_KEY

🚀 Usage

Open and run the notebook:

jupyter notebook crewai_debugger.ipynb

Run all cells top to bottom. The crew will execute sequentially:

  1. Code Analyzer evaluates the buggy code and lists all errors.
  2. Code Corrector applies fixes based on the error report.
  3. The final corrected code is displayed in the Run the Pipeline cell.

To debug different code, update the BUGGY_CODE variable in Cell 3.

🔧 Configuration

| Variable | Description | Required | |---|---|---| | OPENAI_API_KEY | Your OpenAI API key (paid plan required) | ✅ | | OPENAI_MODEL_NAME | Model to use (default: gpt-4o) | ❌ |

Set these in your .env file (use .env.example as a template).

CodeInterpreterTool requires Docker Desktop to be running. Start it before executing the pipeline cell.

📄 License

This project is licensed under the MIT License.

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://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/snapshot"
curl -s "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/contract"
curl -s "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/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.

Related Agents

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

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Agent hubMore from this sourceOpenClaw agents
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://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-04-17T00:48:15.341Z"
    }
  },
  "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": "Sanjai S0",
    "href": "https://github.com/SANJAI-s0/crewai-code-debugger",
    "sourceUrl": "https://github.com/SANJAI-s0/crewai-code-debugger",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T06:04:07.858Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T06:04:07.858Z",
    "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-sanjai-s0-crewai-code-debugger/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-sanjai-s0-crewai-code-debugger/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

Ads related to crewai-code-debugger and adjacent AI workflows.