Xpersona

Crawler Summary

TestAutomator-Agentic-Baisc answer-first brief

Multi-agent system orchestrating the complete STLC using CrewAI TestAutomator A multi-agent system that orchestrates the complete Software Testing Life Cycle (STLC) using **CrewAI**. It autonomously converts product requirement documents (PRDs, BRDs, SRS, user stories) into structured requirements, test plans, test cases, automation scripts, code reviews, execution results, and final release readiness reports. Architecture TestAutomator uses 7 specialized AI agents in a sequentia Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

TestAutomator-Agentic-Baisc 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

TestAutomator-Agentic-Baisc

Multi-agent system orchestrating the complete STLC using CrewAI TestAutomator A multi-agent system that orchestrates the complete Software Testing Life Cycle (STLC) using **CrewAI**. It autonomously converts product requirement documents (PRDs, BRDs, SRS, user stories) into structured requirements, test plans, test cases, automation scripts, code reviews, execution results, and final release readiness reports. Architecture TestAutomator uses 7 specialized AI agents in a sequentia

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

Bibhusundar

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Unpublished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

Bibhusundar

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

Requirement Agent
      │
      ▼
  Planning Agent
      │
      ▼
  Designer Agent
      │
      ▼
  Automator Agent
      │
      ▼
  Code Review Agent
      │
      ▼
  Test Lab Agent
      │
      ▼
  Test Report Agent

bash

# 1. Clone and enter the project
git clone <repo-url> TestAutomator
cd TestAutomator

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

# 3. Configure LLM (edit .env)
# For Ollama (recommended - free):
#   OPENAI_API_BASE=http://localhost:11434/v1
#   OPENAI_MODEL_NAME=llama3.2
#   OPENAI_API_KEY=ollama
#
# For OpenAI:
#   OPENAI_API_KEY=sk-...
#   OPENAI_MODEL_NAME=gpt-4o

# 4. Place your requirement documents in data/
#    Supported: PDF, DOCX, XLSX, TXT, MD

# 5. Run the pipeline
python src/main.py

text

TestAutomator/
├── .env                          # Configuration (API keys, model, paths)
├── .gitignore                    # Git ignore rules
├── requirements.txt              # Python dependencies
├── README.md                     # This file
├── Sub-AgentSpec/                # Full specifications for all 7 agents
│   ├── RequirementAgent.md
│   ├── PlanningAgent.md
│   ├── DesignerAgent.md
│   ├── AutomatorAgent.md
│   ├── CodeReviewAgent.md
│   ├── TestExecutionAgent.md
│   ├── TestReportAgent.md
│   └── TestAutomatorCrew.md
├── Skills/                       # CrewAI skill files (agent knowledge)
│   └── all/
│       ├── playwright-e2e-testing/SKILL.md
│       ├── test-plan-generation/SKILL.md
│       └── code-review-excellence/SKILL.md
├── data/                         # [INPUT] Place PRD/BRD/user story files here
├── context/                      # [OPTIONAL] Context files per agent
├── output/                       # [OUTPUT] Generated artifacts
│   ├── Requirement Agent/
│   ├── Planning Agent/
│   ├── Designer Agent/
│   ├── Automator Agent/
│   ├── Code Review Agent/
│   ├── Test Lab Agent/
│   └── Test Report Agent/
├── agents/                       # Agent definitions (role, goal, backstory)
├── tasks/                        # Task definitions (description, expected output)
├── tools/                        # Custom CrewAI tools
└── src/
    ├── orchestrator.py           # Crew orchestration & pipeline runner
    └── main.py                   # Entry point

bash

# Install Ollama from https://ollama.com
ollama pull llama3.2

env

OPENAI_API_BASE=http://localhost:11434/v1
OPENAI_MODEL_NAME=llama3.2
OPENAI_API_KEY=ollama

env

OPENAI_API_KEY=sk-your-key-here
OPENAI_MODEL_NAME=gpt-4o

Docs & README

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

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

Multi-agent system orchestrating the complete STLC using CrewAI TestAutomator A multi-agent system that orchestrates the complete Software Testing Life Cycle (STLC) using **CrewAI**. It autonomously converts product requirement documents (PRDs, BRDs, SRS, user stories) into structured requirements, test plans, test cases, automation scripts, code reviews, execution results, and final release readiness reports. Architecture TestAutomator uses 7 specialized AI agents in a sequentia

Full README

TestAutomator

A multi-agent system that orchestrates the complete Software Testing Life Cycle (STLC) using CrewAI. It autonomously converts product requirement documents (PRDs, BRDs, SRS, user stories) into structured requirements, test plans, test cases, automation scripts, code reviews, execution results, and final release readiness reports.

Architecture

TestAutomator uses 7 specialized AI agents in a sequential pipeline:

Requirement Agent
      │
      ▼
  Planning Agent
      │
      ▼
  Designer Agent
      │
      ▼
  Automator Agent
      │
      ▼
  Code Review Agent
      │
      ▼
  Test Lab Agent
      │
      ▼
  Test Report Agent

Each agent's output feeds directly into the next, creating a fully automated STLC workflow.

Sub-Agents

| # | Agent | Input | Output | |---|-------|-------|--------| | 1 | Requirement Agent | PRD/BRD/SRS/user story files from data/ | Structured requirements, RTM, JSON output | | 2 | Planning Agent | Structured requirements + RTM | Test plan, strategy, scope, risk assessment, schedule | | 3 | Designer Agent | Test plan + requirements | Test scenarios, manual/API/UI test cases, automation candidates | | 4 | Automator Agent | Approved test cases + automation candidates | Playwright/POM scripts, API tests, config files, test suites | | 5 | Code Review Agent | Automation scripts | Code review report, quality score, pass/fail decision | | 6 | Test Lab Agent | Approved scripts + test cases | Execution results, logs, failure classification, defect candidates | | 7 | Test Report Agent | Execution results | Test summary, quality metrics, Go/No-Go recommendation |

Prerequisites

  • Python 3.11+
  • Ollama installed (for local LLM) or OpenAI API key

Quick Start

# 1. Clone and enter the project
git clone <repo-url> TestAutomator
cd TestAutomator

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

# 3. Configure LLM (edit .env)
# For Ollama (recommended - free):
#   OPENAI_API_BASE=http://localhost:11434/v1
#   OPENAI_MODEL_NAME=llama3.2
#   OPENAI_API_KEY=ollama
#
# For OpenAI:
#   OPENAI_API_KEY=sk-...
#   OPENAI_MODEL_NAME=gpt-4o

# 4. Place your requirement documents in data/
#    Supported: PDF, DOCX, XLSX, TXT, MD

# 5. Run the pipeline
python src/main.py

Project Structure

TestAutomator/
├── .env                          # Configuration (API keys, model, paths)
├── .gitignore                    # Git ignore rules
├── requirements.txt              # Python dependencies
├── README.md                     # This file
├── Sub-AgentSpec/                # Full specifications for all 7 agents
│   ├── RequirementAgent.md
│   ├── PlanningAgent.md
│   ├── DesignerAgent.md
│   ├── AutomatorAgent.md
│   ├── CodeReviewAgent.md
│   ├── TestExecutionAgent.md
│   ├── TestReportAgent.md
│   └── TestAutomatorCrew.md
├── Skills/                       # CrewAI skill files (agent knowledge)
│   └── all/
│       ├── playwright-e2e-testing/SKILL.md
│       ├── test-plan-generation/SKILL.md
│       └── code-review-excellence/SKILL.md
├── data/                         # [INPUT] Place PRD/BRD/user story files here
├── context/                      # [OPTIONAL] Context files per agent
├── output/                       # [OUTPUT] Generated artifacts
│   ├── Requirement Agent/
│   ├── Planning Agent/
│   ├── Designer Agent/
│   ├── Automator Agent/
│   ├── Code Review Agent/
│   ├── Test Lab Agent/
│   └── Test Report Agent/
├── agents/                       # Agent definitions (role, goal, backstory)
├── tasks/                        # Task definitions (description, expected output)
├── tools/                        # Custom CrewAI tools
└── src/
    ├── orchestrator.py           # Crew orchestration & pipeline runner
    └── main.py                   # Entry point

Configuration

Edit .env to configure:

| Variable | Description | Default | |----------|-------------|---------| | OPENAI_API_KEY | API key (or ollama for local) | ollama | | OPENAI_API_BASE | API base URL | http://localhost:11434/v1 | | OPENAI_MODEL_NAME | LLM model | llama3.2 | | INPUT_DATA_DIR | Input documents folder | data | | OUTPUT_DIR | Output artifacts folder | output | | SKILLS_DIR | Skill files folder | Skills | | CONTEXT_DIR | Context files folder | context |

Running with Ollama (Local, Free)

# Install Ollama from https://ollama.com
ollama pull llama3.2

Then set .env:

OPENAI_API_BASE=http://localhost:11434/v1
OPENAI_MODEL_NAME=llama3.2
OPENAI_API_KEY=ollama

Running with OpenAI

OPENAI_API_KEY=sk-your-key-here
OPENAI_MODEL_NAME=gpt-4o

Customization

  • Skill files: Add .SKILL.md files in Skills/all/<skill-name>/SKILL.md to guide agent behavior. The name in frontmatter must match the directory name (lowercase kebab-case).
  • Agent behavior: Modify agent role, goal, and backstory in agents/<agent_name>.py
  • Task scope: Adjust task descriptions and expected outputs in tasks/<agent_name>.py
  • Input data: Place any combination of PDF, DOCX, XLSX, TXT, or MD files in data/

Input File Support

| Format | Library | Notes | |--------|---------|-------| | PDF | pdfplumber | Text extraction from PDFs | | DOCX | python-docx | Word documents | | XLSX | openpyxl | Excel spreadsheets | | TXT/MD | Built-in | Plain text and markdown |

License

MIT

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-bibhusundar-testautomator-agentic-baisc/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/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-bibhusundar-testautomator-agentic-baisc/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T22:49:05.632Z"
    }
  },
  "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": "Bibhusundar",
    "href": "https://github.com/BibhuSundar/TestAutomator-Agentic-Baisc",
    "sourceUrl": "https://github.com/BibhuSundar/TestAutomator-Agentic-Baisc",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T18:18:10.729Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T18:18:10.729Z",
    "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-bibhusundar-testautomator-agentic-baisc/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-bibhusundar-testautomator-agentic-baisc/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
  }
]

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