AI Agent Stack Builder

v1.0.0

Intelligent recommendation system that generates optimal AI agent technology stacks based on project requirements, constraints, and team expertise.

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Install the skill "AI Agent Stack Builder" (krishnakumarmahadevan-cmd/toolweb-ai-agent-stack-builder) from ClawHub.
Skill page: https://clawhub.ai/krishnakumarmahadevan-cmd/toolweb-ai-agent-stack-builder
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Use only the metadata you can verify from ClawHub; do not invent missing requirements.
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Security Scan
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high confidence
Purpose & Capability
Name, description, SKILL.md content, and openapi.json all describe a stack-recommendation API and require no unrelated binaries, credentials, or system access — the requested surface is proportional to the stated purpose.
Instruction Scope
SKILL.md defines request/response schemas and endpoints for generating recommendations and does not instruct the agent to read files, environment variables, or system state. Note: formData accepts fields like userId and additionalNotes which could contain sensitive information; the skill does not explain where requests are sent (no base URL), so be cautious about providing sensitive data when invoking.
Install Mechanism
No install spec and no code files that would be written to disk; instruction-only skills are lowest-risk from an install perspective.
Credentials
The skill declares no required environment variables, credentials, or config paths. No disproportionate credential access is requested.
Persistence & Privilege
always is false (default), and there is no indication the skill modifies agent/system configurations or requests persistent presence or elevated privileges.
Assessment
This skill appears coherent and self-contained: it documents a recommendation API and does not request credentials or install code. However, the source and homepage are unknown — before using it, confirm where the API requests will be sent (there's no base URL), avoid sending sensitive or regulated data (e.g., PII, secrets, health records) in formData, and test with non-sensitive sample inputs first. If you plan to use this in production, prefer skills from a known source or review the origin and hosting details so you can verify privacy and security guarantees.

Like a lobster shell, security has layers — review code before you run it.

latestvk975hnc8vv0ekc188bq1w1rcsd843ees
108downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0

Overview

The AI Agent Stack Builder is an intelligent recommendation engine designed to help development teams select the optimal technology stack for building AI agents. By analyzing project requirements—including type, expected user load, budget constraints, latency requirements, deployment preferences, and team expertise—the system provides curated recommendations for frameworks, large language models (LLMs), and supporting technologies.

This tool addresses a critical pain point in modern AI development: the overwhelming number of choices when building agent-based systems. Whether you're developing a customer service chatbot, autonomous research agent, or data analysis tool, the Stack Builder evaluates your unique constraints and generates a prioritized set of recommendations tailored to your situation.

The API is ideal for development teams, AI architects, technical leads, and organizations evaluating AI agent solutions who need objective, data-driven guidance on technology selection aligned with their specific operational and business constraints.

Usage

Sample Request:

{
  "formData": {
    "projectType": "customer_service_chatbot",
    "userLoad": "high",
    "budget": "medium",
    "latency": "low",
    "deployment": "cloud",
    "expertise": "intermediate",
    "capabilities": ["natural_language_understanding", "context_retention", "multi_turn_conversation"],
    "security": ["data_encryption", "role_based_access_control"],
    "additionalNotes": "Need HIPAA compliance for healthcare customer service"
  },
  "sessionId": "sess_abc123def456",
  "userId": 12345,
  "timestamp": "2024-01-15T14:30:00Z"
}

Sample Response:

{
  "recommendation": {
    "frameworks": [
      {
        "name": "LangChain",
        "priority": 1,
        "reasoning": "Excellent for multi-turn conversations with memory management and integrations",
        "suitability_score": 0.95
      },
      {
        "name": "LlamaIndex",
        "priority": 2,
        "reasoning": "Strong context retention and retrieval capabilities",
        "suitability_score": 0.88
      }
    ],
    "llms": [
      {
        "name": "GPT-4",
        "provider": "OpenAI",
        "priority": 1,
        "reasoning": "Superior NLU and context understanding for customer interactions",
        "cost_per_1m_tokens": 0.03,
        "latency_ms": 200
      },
      {
        "name": "Claude 3 Sonnet",
        "provider": "Anthropic",
        "priority": 2,
        "reasoning": "Strong privacy stance and cost-effective alternative",
        "cost_per_1m_tokens": 0.003,
        "latency_ms": 250
      }
    ],
    "supporting_technologies": [
      {
        "category": "vector_database",
        "recommendation": "Pinecone",
        "reasoning": "Managed solution suitable for cloud deployment with high availability"
      },
      {
        "category": "monitoring",
        "recommendation": "Datadog",
        "reasoning": "Comprehensive monitoring for latency-sensitive applications"
      }
    ],
    "compliance_notes": "Verify LLM provider's HIPAA BAA requirements; consider on-premise deployment for sensitive data handling",
    "estimated_monthly_cost": 1500,
    "implementation_timeline_weeks": 4
  }
}

Endpoints

GET /

Root / Health Check

Returns a health status of the API service.

ParameterTypeRequiredDescription
NoneNo parameters required

Response: 200 OK

{
  "status": "healthy",
  "version": "1.0.0"
}

POST /api/agent/stack

Generate Stack Recommendation

Generates an AI agent technology stack recommendation based on project requirements and constraints.

ParameterTypeRequiredDescription
formDataObjectProject requirements and constraints
formData.projectTypestringType of AI agent project (e.g., "customer_service_chatbot", "research_agent", "data_analysis_agent")
formData.userLoadstringExpected user load level ("low", "medium", "high")
formData.budgetstringBudget constraint ("low", "medium", "high")
formData.latencystringLatency requirement ("low", "medium", "high")
formData.deploymentstringDeployment environment ("cloud", "on_premise", "hybrid", "edge")
formData.expertisestringTeam's technical expertise level ("beginner", "intermediate", "advanced")
formData.capabilitiesarray[string]OptionalRequired AI capabilities (e.g., "natural_language_understanding", "context_retention", "function_calling")
formData.securityarray[string]OptionalSecurity and compliance requirements (e.g., "data_encryption", "role_based_access_control", "audit_logging")
formData.additionalNotesstringOptionalAdditional context or special requirements
sessionIdstringUnique session identifier for tracking
userIdintegerOptionalUser identifier for personalization
timestampstringRequest timestamp in ISO 8601 format

Response: 200 OK

{
  "recommendation": {
    "frameworks": [...],
    "llms": [...],
    "supporting_technologies": [...],
    "compliance_notes": "string",
    "estimated_monthly_cost": 0,
    "implementation_timeline_weeks": 0
  }
}

Error Response: 422 Unprocessable Entity

{
  "detail": [
    {
      "loc": ["body", "formData", "projectType"],
      "msg": "field required",
      "type": "value_error.missing"
    }
  ]
}

GET /api/frameworks

Get Available Frameworks

Retrieves the list of available AI agent frameworks that the system can recommend.

ParameterTypeRequiredDescription
NoneNo parameters required

Response: 200 OK

{
  "frameworks": [
    {
      "name": "LangChain",
      "version": "0.1.0",
      "category": "orchestration",
      "description": "Framework for building applications with LLMs",
      "maturity": "production"
    },
    {
      "name": "LlamaIndex",
      "version": "0.10.0",
      "category": "retrieval",
      "description": "Data framework for LLM applications",
      "maturity": "production"
    }
  ]
}

GET /api/llms

Get Available LLMs

Retrieves the list of available large language models that the system can recommend.

ParameterTypeRequiredDescription
NoneNo parameters required

Response: 200 OK

{
  "llms": [
    {
      "name": "GPT-4",
      "provider": "OpenAI",
      "type": "closed_source",
      "context_window": 128000,
      "cost_per_1m_tokens": 0.03,
      "latency_ms": 200
    },
    {
      "name": "Claude 3 Opus",
      "provider": "Anthropic",
      "type": "closed_source",
      "context_window": 200000,
      "cost_per_1m_tokens": 0.015,
      "latency_ms": 300
    }
  ]
}

Pricing

PlanCalls/DayCalls/MonthPrice
Free550Free
Developer20500$39/mo
Professional2005,000$99/mo
Enterprise100,0001,000,000$299/mo

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