VANE-SPACE-SLA (v1.0) 🛰️ - BobOnboard Intelligent Deterministic Multi-Gate Telemetry

[MD_ABUL_HOSSAIN]

# VANE-SPACE-SLA (v1.0)

**Deterministic Multi-Gate Telemetry Validation & Strict Prompt Grounding Toolkit**

*Demonstration / Portfolio Project*

A lightweight, self-contained Python toolkit that demonstrates multi-gate telemetry validation and strict prompt grounding concepts.

All external AI and infrastructure services are **intentionally simulated** so the project remains fully runnable without any paid or external dependencies.

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## What This Project Actually Does

- Simulates multi-gate telemetry validation

- Provides a strict / moderate / soft prompt grounding builder

- Uses environment variables (no hardcoded secrets)

- Includes structured logging

- Comes with a complete pytest test suite

- Has GitHub Actions CI

This is **not** a production RAG system, and it does **not** call real IBM watsonx, Milvus, FAISS, Redis, or PostgreSQL services.

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## Quick Start

```bash

git clone GitHub - AnticipatedD/VANE-SPACE-SLA: A Deterministic Zero-Trust Anomaly Detection and Telemetry Engine for Mission-Critical Spacecraft Operations. · GitHub

cd VANE-SPACE-SLA

python -m venv .venv

source .venv/bin/activate # Windows: .venv\Scripts\activate

pip install -r requirements.txt

cp .env.example .env

pytest --cov=. --cov-report=term

python vane_space_init.py

```

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## Project Structure

VANE-SPACE-SLA/

├── vane_space_init.py

├── strict_prompt_builder.py

├── requirements.txt

├── .env.example

├── .github/workflows/ci.yml

├── tests/

│ ├── test_vane_space_init.py

│ └── test_strict_prompt_builder.py

└── README.md

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## Author

**MD ABUL HOSSAIN**

IBM Business Partner Plus

European F&T Expert ID: EX2026D1473148

Web of Science ResearcherID: QQZ-6739-2026 | ORCID: 0009-0004-4378-5298

Microsoft Learn Level 10 (90 badges, 17 trophies)

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## License

MIT

### Next actions (in order)

1. Replace the entire `README.md` with the text above.

2. Add / replace the other files I gave you earlier:

• `requirements.txt`

• `.env.example`

• Updated `vane_space_init.py`

• Updated `strict_prompt_builder.py`

• `tests/test_vane_space_init.py`

• `tests/test_strict_prompt_builder.py`

  • `.github/workflows/ci.yml`

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© 2026 MD ABUL HOSSAIN. All Rights Reserved

[Hakob_Arzumanyan]

Hello, and thanks for sharing. The README is the best part of this. Saying outright that the services are simulated and that it isn’t a production RAG system is more honesty than most portfolio projects manage. Two things around it weaken that though. Your GitHub description calls it a telemetry engine for mission-critical spacecraft operations, which is a very different promise. And the architecture diagram shows IBM Bob 2.0, voice_agents.py and m2m-oauth-isolation.html, none of which appear anywhere in your file list. Both are quick fixes. Wish you the best of luck.

[MD_ABUL_HOSSAIN]

@Hakob_Arzumanyan actually it’s really rare to find a codes or a person who develop and act with their honesty seems like something missing or lack of this and that. I have copied and pasted my README.md file with reliable and whatever sources i have and used to built this repo. Regarding your all other files questions it’s alredy there and you can find everything if you go to VANE-SPACE-SLA. Please click on my repo link and discover what’s it got there.

Live GitHub Pages: VANE-SPACE-SLA) MATRIX- Vaerified Secured Node Latency.

VANE-SPACE-SLA (v1.0)- BobOnboard
Intelligent Multi-Agent Repository Onboarding System
Powered by IBM Bob 2.0

Submitted by: MD ABUL HOSSAIN
IBM Business Partner Plus | European F&T ExpertID: EX2026D1473148 | Catagory B Senior ResearcherID: QQZ-6739-2026 | ORCID: 0009-0004-4378-5298 | AlphaNova Tech Global Leaderboard Rank # 28 and Individual Rank 57/873. MSLearn 90 Badges and 17 Trophies reached Level 10.

1. Problem Statement:

Onboarding to a new codebase remains one of the most time-consuming and error-prone stages in the software development lifecycle. Developers routinely spend 3 to 6 hours (sometimes multiple days) performing the following manual tasks:

1. Reading and interpreting the README
2. Exploring the folder structure
3. Identifying installation and run instructions
4. Discovering existing tests and coverage gaps.
5. Detecting hidden risks (hardcoded secrets, missing CI, weak documentation, etc.)

This process creates unnecessary friction, delays the first meaningful contribution, increases the chance of mistakes, and places repeated burden on existing team members.

2. Solution: VANE-SPLACE-SLA(v1.0) - BobOnboard Intelligent multi-agent system - Powered by IBM Bob 2.0 that automatically analyzes any software repository and produces a complete, actionable onboarding package within minutes.It transforms a slow, manual, and error-prone process into a fast, structured, and reliable workflow.

Core Capabilities Used from IBM Bob 2.0
Agent Mode → Main Orchestrator Agent that plans and coordinates the entire analysis
Subagents / Parallel Tasks → Multiple specialized agents work simultaneously
Document Understanding → Deep reading of README, source code, tests, and configuration files

**3. System Architecture **

1. Main Agent (Orchestrator)
   Receives the target repository, creates an analysis plan, launches subagents in parallel, collects results, and generates the final onboarding report.

Parallel Subagents:
Subagent 1. Responsibility
2. Structure Analyzer
3. Maps directory structure and identifies key files
5.Setup & Dependency Agent
6.Extracts installation and execution steps.
7.Test Discovery Agent.

Locates existing tests and highlights coverage gaps
Risk & Quality Agent
Detects security issues, missing CI, and documentation gaps
Onboarding Guide Writer
Produces a clear, step-by-step onboarding document

4. What BobOnboard Delivers
When the process completes, the developer receives a structured onboarding package containing:

1. Clear project summary in plain language.
2. Exact setup and run instructions.
3. Recommended file reading order.
4. Current test status and missing test areas.
5. Risk and quality report.
6. Personalized first-week contribution checklist
7. Ready-to-use onboarding guide

5. Measurable Impact

Metric- Average onboarding time
Traditional Approach- 3-6 hours
With BobOnboard- 15-20 minutes
Improvement- ~85% reduction

Metric- Manual file exploration effort
Traditional Approach - Very High
With BobOnboard - Minimal
Improvement - Major reduction

Metric - Risk of missing critical information
Traditional Approach - High
With BobOnboard - Very Low
Improvement - Strongly reduced
Time to first meaningful

Metric - contribution
Traditional Approach - 1–3 days
With BobOnboard - Same day possible
Improvement - Significant gain

6. Demonstration Plan
The working prototype demonstration follows these steps:

1. Launch IBM Bob 2.0 and activate BobOnboard.
2. Point the system at a real repository (example used: VANE-SPACE-SLA).
3. The Main Agent analyzes the request and launches multiple subagents in parallel.
4. Document Understanding reads the README, source files, and test files.
5. Subagents complete their specialized tasks simultaneously.
6. The system generates and presents a complete onboarding report.
7. The report clearly highlights time savings and detected risks.

This demonstration shows a full end-to-end improvement of the developer onboarding workflow using Agent Mode, parallel subagents, and document understanding.

7. Why This Solution Fits the Challenge?

1. Solves a real and high-impact developer pain point
2. Clearly leverages IBM Bob 2.0’s advanced capabilities (Agent Mode, Subagents, Document Understanding).
3. Delivers a focused and polished prototype rather than an overly broad system.
4. Provides measurable productivity gains.
5. Can be realistically adopted by engineering teams

8. Conclusion
BobOnboard demonstrates how IBM Bob 2.0 can move beyond simple code generation and actively improve an entire developer workflow.

By combining Agent Mode, parallel subagents, and document understanding, the solution significantly reduces onboarding time, lowers error risk, and accelerates the path to first contribution.