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release: 0.8.5
Version-only: the four version strings move to 0.8.5 and [Unreleased] becomes [0.8.5] — 2026-09-14. Everything it releases is already on main. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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.claude-plugin/marketplace.json

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},
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"metadata": {
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"description": "The trust layer between AI and your data. A governed semantic model for AI-to-database access — every join approved, every metric signed off, every answer with a receipt. Local-first: no infra, no servers, no data leaves your machine.",
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"version": "0.8.4",
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"version": "0.8.5",
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"pluginRoot": "./plugins",
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"tags": ["data", "sql", "governance", "trust-layer", "semantic-model", "local-first", "fair-code"],
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"repository": "https://github.com/AgamiAI/agami-core",
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"name": "agami-core",
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"source": "./plugins/agami",
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"description": "A governed trust layer between AI and your database: every join FK-derived or human-approved, every metric signed off, every answer with a receipt (the SQL, the model version, who vouched for each definition). Runs entirely on your machine via Claude's Bash / Read / Write tools — no MCP server or Python required if you have psql/mysql or DuckDB (an optional local MCP server is available for use from Claude Desktop).",
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"version": "0.8.4",
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"version": "0.8.5",
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"keywords": ["database", "governance", "trust-layer", "semantic-model", "sql", "postgres", "snowflake"],
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"category": "data"
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}

CHANGELOG.md

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user's plugin cache (see [CONTRIBUTING.md](CONTRIBUTING.md)). Each released section
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below corresponds to one such version.
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## [Unreleased]
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## [0.8.5] — 2026-09-14
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### Added
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packages/agami-core/pyproject.toml

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[project]
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name = "agami-core"
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version = "0.8.4"
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version = "0.8.5"
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description = "agami-core — governed semantic model, the shared MCP TOOLS harness, and the unified local query executor."
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readme = "README.md"
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requires-python = ">=3.10"

plugins/agami/.claude-plugin/plugin.json

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{
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"name": "agami-core",
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"description": "The trust layer between AI and your database, so an agent's answers are defensible. Every join, metric, and named filter is confidence-scored and either FK-derived or human-approved via a review dashboard. Every answer ships a SQL receipt showing what ran and which model version it used. Works across Postgres / MySQL / Snowflake / BigQuery / Redshift / SQL Server / Oracle / Databricks / Trino / DuckDB / SQLite. Local-first: credentials, schema, results never leave your machine.",
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"version": "0.8.4",
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"version": "0.8.5",
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"author": {
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"name": "Agami AI",
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"email": "skills@agami.ai",

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