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chore(release): bump version to 0.8.0
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CHANGELOG.md

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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.8.0] - 2026-03-29
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### Added
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- **Claude Code plugin** — distributable plugin with 7 domain skills (bearing diagnosis, gear analysis, quick screening, report generation, anomaly detection, signal management, documentation search), 2 autonomous agents (`diagnostic-pipeline`, `signal-explorer`), and 3 slash commands (`/pm-diagnose`, `/pm-screen`, `/pm-report`). Installable from the Claude Code marketplace.
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- **Prognostics sub-package**`src/prognostics/` with `RULEstimator` (Remaining Useful Life) and `TrendAnalyzer` with confidence intervals — ISO 13374 Block 5 implementation.
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- **Decision support sub-package**`src/decision_support/` with `AlertManager`, `MaintenanceRecommendations`, and evidence-based `DiagnosisPipeline` — ISO 13374 Block 6 advisory layer.
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- **Phase 1 modular refactoring** — monolithic server split into `mcp_tools/` (acquisition, analysis, diagnostics, report, prompts), `signal_acquisition/`, `signal_processing/`, `diagnostics/`, `prognostics/`, `decision_support/` sub-packages following ISO 13374 six-block architecture.
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- **Jupyter notebooks** — 3 interactive notebooks: getting started, bearing diagnostics, condition monitoring.
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- **Guided workflow prompts** — 4 MCP prompt endpoints: `diagnose_bearing_prompt`, `diagnose_gear_prompt`, `quick_diagnostic_report_prompt`, `analyze_anomalies_prompt`.
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### Changed
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- Total MCP endpoints expanded to **48** (from 24).
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- README strategically redesigned: pitch-first, 60% shorter, engineer/developer split quickstarts.
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- GitHub Pages updated: Tools at a Glance section, ISO 13374 six-block architecture diagram, standards compliance strip, Prognostics & Decision Intelligence feature cards.
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- Test coverage at **86%** across 20+ test files.
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## [0.7.1] - 2025-07-15
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### Added

docs/index.html

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"applicationCategory": "EngineeringApplication",
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"applicationSubCategory": "Predictive Maintenance, Condition Monitoring, Industrial AI",
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"operatingSystem": "Windows, macOS, Linux",
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"softwareVersion": "0.7.1",
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"softwareVersion": "0.8.0",
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"license": "https://opensource.org/licenses/MIT",
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"url": "https://lgdimaggio.github.io/predictive-maintenance-mcp/",
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"codeRepository": "https://github.com/LGDiMaggio/predictive-maintenance-mcp",
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title = {Predictive Maintenance MCP Server},
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author = {Di Maggio, Luigi Gianpio},
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year = {2025},
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version = {0.7.1},
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version = {0.8.0},
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url = {https://github.com/LGDiMaggio/predictive-maintenance-mcp},
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doi = {10.5281/zenodo.17611542}
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}</div>

pyproject.toml

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[project]
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name = "predictive-maintenance-mcp"
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version = "0.7.1"
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version = "0.8.0"
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description = "AI agent for predictive maintenance & condition monitoring — Open-source MCP server and Claude Code plugin with 48 endpoints for vibration analysis, bearing fault detection, ISO 20816 compliance, and ML anomaly detection via natural language"
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readme = "README.md"
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authors = [

src/__init__.py

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Package name: predictive_maintenance_mcp (mapped from src/ directory).
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"""
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__version__ = "0.7.1"
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__version__ = "0.8.0"
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__author__ = "Luigi Gianpio Di Maggio"
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__license__ = "MIT"
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