Xpersona

Crawler Summary

interview_coach answer-first brief

Interview Coach is a multi-agent system built using crewAi that, given your resume and a job description, crafts a mock interview and evaluates your answers. Interview Coach Welcome to the **Interview Coach**, an advanced AI-powered interview coaching system built with $1. This system automates the end-to-end mock interview process—from analyzing job descriptions (JD) and resumes to generating tailored questions and producing comprehensive performance reports. Features * **AI-Powered Mock Interviews**: Generates realistic, high-signal questions by cross-referencing resume Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/16/2026.

Freshness

Last checked 4/16/2026

Best For

interview_coach 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

interview_coach

Interview Coach is a multi-agent system built using crewAi that, given your resume and a job description, crafts a mock interview and evaluates your answers. Interview Coach Welcome to the **Interview Coach**, an advanced AI-powered interview coaching system built with $1. This system automates the end-to-end mock interview process—from analyzing job descriptions (JD) and resumes to generating tailored questions and producing comprehensive performance reports. Features * **AI-Powered Mock Interviews**: Generates realistic, high-signal questions by cross-referencing resume

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Apr 16, 2026

Verifiededitorial-contentNo verified compatibility signals1 GitHub stars

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 4/16/2026.

1 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 16, 2026

Vendor

Zakey Team 1

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Unpublished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. 1 GitHub stars reported by the source. Last updated 4/16/2026.

View Source

Setup snapshot

git clone https://github.com/Zakey-Team-1/interview_coach.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

Zakey Team 1

profilemedium
Observed Apr 16, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 16, 2026Source linkProvenance
Adoption (1)

Adoption signal

1 GitHub stars

profilemedium
Observed Apr 16, 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

text

interview_coach/
├── src/
│   ├── interview_coach/
│   │   ├── api/                 # Stateless FastAPI backend
│   │   ├── crews/               # CrewAI agent & task definitions
│   │   │   ├── supervisor/      # JD analysis crew
│   │   │   ├── interview/       # Question generation crew
│   │   │   └── evaluation/      # Response evaluation crew
│   │   ├── questions_flow.py    # Main orchestration flow
│   │   └── main.py              # Entry point
│   ├── rag/                     # RAG system logic
│   └── tools/                   # Custom tools for agents

bash

git clone [https://github.com/Zakey-Team-1/interview_coach]
cd interview_coach
uv tool install crewai
crewai install

bash

uv run serve

Docs & README

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

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Interview Coach is a multi-agent system built using crewAi that, given your resume and a job description, crafts a mock interview and evaluates your answers. Interview Coach Welcome to the **Interview Coach**, an advanced AI-powered interview coaching system built with $1. This system automates the end-to-end mock interview process—from analyzing job descriptions (JD) and resumes to generating tailored questions and producing comprehensive performance reports. Features * **AI-Powered Mock Interviews**: Generates realistic, high-signal questions by cross-referencing resume

Full README

Interview Coach

Welcome to the Interview Coach, an advanced AI-powered interview coaching system built with crewAI. This system automates the end-to-end mock interview process—from analyzing job descriptions (JD) and resumes to generating tailored questions and producing comprehensive performance reports.

Features

  • AI-Powered Mock Interviews: Generates realistic, high-signal questions by cross-referencing resumes with specific JD requirements.
  • RAG-Enhanced Context: Ingests PDF resumes into a RAG system to ensure questions are grounded in the candidate's actual experience.
  • Parallel Processing: Uses parallel agent execution to clean JDs and generate questions simultaneously, reducing latency.
  • Comprehensive Evaluation: A dedicated crew of agents evaluates responses to produce a detailed report covering strengths, weaknesses, and actionable advice.
  • Stateless & Scalable: A FastAPI backend designed for Cloud Run, utilizing Supabase for persistent data storage.

Architecture

The system is orchestrated using CrewAI Flows, following a structured 5-step pipeline:

  1. Preprocessing & Ingestion: In parallel, the system cleans/preprocesses the Job Description and ingests the Resume PDF into the RAG vector store.
  2. Topic Identification: A Supervisor Agent analyzes the cleaned JD to identify 5-7 core topics/skill sets required for the role.
  3. Parallel Question Generation: Each topic is passed to a Question Generation Agent in parallel. This agent uses relevant snippets from the Resume (via RAG) to create tailored, technical interview questions.
  4. Frontend Delivery: The curated list of questions is dispatched to the Google AI Studio-based frontend.
  5. Evaluation Flow: Once the user submits their answers, a Crew of Agents evaluates the responses against the JD to produce a final report including a summary, main strengths, weaknesses, and coaching advice.

Tech Stack

  • Framework: crewAI (Agent Orchestration & Flows)
  • Backend: FastAPI (Python)
  • Frontend: Google AI Studio
  • Database: Supabase (Postgres)
  • Embeddings: Google Gemini Embeddings 001
  • Deployment: Google Cloud Run (CI/CD via GCP)

Observability & Monitoring

To ensure the reliability of the multi-agent orchestration and to monitor LLM costs and latency, this project integrates LangFuse.

  • Detailed Tracing: Every step of the CrewAI Flow is traced.
  • Performance Metrics: Track the latency of parallel agent execution and token usage for Google Gemini models.

📡 API & Infrastructure

Stateless Backend

The FastAPI backend is entirely stateless. It receives data via API calls, processes it through the CrewAI agents, and returns the response. This allows for seamless scaling on Google Cloud Run.

Deployment (CI/CD)

The project is deployed directly to Google Cloud Run from the GitHub repository.

  • Pipeline: A CI/CD pipeline is triggered on every commit to the master branch.
  • Infrastructure: Managed via Artifact Registry and Cloud Run for high availability.

📂 Project Structure

interview_coach/
├── src/
│   ├── interview_coach/
│   │   ├── api/                 # Stateless FastAPI backend
│   │   ├── crews/               # CrewAI agent & task definitions
│   │   │   ├── supervisor/      # JD analysis crew
│   │   │   ├── interview/       # Question generation crew
│   │   │   └── evaluation/      # Response evaluation crew
│   │   ├── questions_flow.py    # Main orchestration flow
│   │   └── main.py              # Entry point
│   ├── rag/                     # RAG system logic
│   └── tools/                   # Custom tools for agents

⚙️ Installation & Setup

Ensure you have Python >=3.10 <3.14 and UV installed.

  1. Clone and Install:
git clone [https://github.com/Zakey-Team-1/interview_coach]
cd interview_coach
uv tool install crewai
crewai install

  1. Environment Variables: Create a copy from the .env.example file named .env and fill it

  2. Run Locally:

uv run serve

The API will be available at http://localhost:8080. Access the interactive docs at /docs.

🤝 Contributing

Contributions are welcome! Please feel free to submit issues or pull requests to improve the agent prompts or the orchestration flow.

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://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/snapshot"
curl -s "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/contract"
curl -s "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/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 6d 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-zakey-team-1-interview-coach/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T04:09:48.206Z"
    }
  },
  "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": "Zakey Team 1",
    "category": "vendor",
    "href": "https://github.com/Zakey-Team-1/interview_coach",
    "sourceUrl": "https://github.com/Zakey-Team-1/interview_coach",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:44.792Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:44.792Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "traction",
    "label": "Adoption signal",
    "value": "1 GitHub stars",
    "category": "adoption",
    "href": "https://github.com/Zakey-Team-1/interview_coach",
    "sourceUrl": "https://github.com/Zakey-Team-1/interview_coach",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-16T06:46:44.792Z",
    "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://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-zakey-team-1-interview-coach/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

Ads related to interview_coach and adjacent AI workflows.