Agent-OS is a governance-first kernel for AI agents — a Python framework providing policy enforcement, semantic intent classification, identity management, and execution control for autonomous AI agents. Architecture: 4-layer modular kernel Framework adapters route intervention points through HostSession and receive PolicyEvaluation. Raise the canonical PolicyViolationError.from_evaluation_result(result) for denied or escalated results. Hosts should surface str(error) and use error.evaluation_result.reason_code for structured handling. Use conventional commits: feat:, fix:, docs:, test:, refactor:, chore:
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agent-governance-python/ is the top-level home for first-party published Python packages in Agent Governance Toolkit. Use this directory for reusable SDK/package surfaces that are meant to be consumed directly by external Python users. Applications, dashboards, demos, and larger runtime/product assemblies should stay in the repo root, examples/, or other existing homes unless maintainers explicitly decide to promote them into this package workspace. - Prefer this directory for first-party Python packages that are published independently. - Keep package names, import paths, and…
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Agent-SRE is an SRE toolkit for AI agent reliability — providing SLO management, error budgets, chaos engineering, progressive delivery, cost guardrails, incident management, and observability for autonomous AI agents. Key engines: Use conventional commits: feat:, fix:, docs:, test:, refactor:, chore:
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Agent Governance Toolkit is a multi-package OSS monorepo for runtime governance of AI agents: policy enforcement, zero-trust identity, execution sandboxing, SRE, compliance, examples, docs, demos, SDKs, and publishing pipelines. Use this file for repository-wide routing. When you enter a subdirectory that has its own AGENTS.md, that narrower file takes precedence. This routing reflects the repo as it exists today while reserving room for approved language SDK migrations. Language SDKs may live in standalone top-level directories at the repository root. For…
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The docs/ tree powers the published documentation site for Agent Governance Toolkit: reference material, tutorials, architecture docs, threat modeling, compliance content, package pages, and integration guides. - Be precise and honest; do not claim a feature is shipped unless the repo actually contains it. - Prefer updating an existing page over creating a near-duplicate page. - Use repo-relative links that work from the current document location. - Match existing tone: technical, direct, and evidence-based. - Keep package names, CLI commands,…
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The examples/ directory is the preferred place for runnable, self-contained integrations and worked examples. For OSS contributors, examples are often the best starting point for proposing support for a new framework or ecosystem tool. Use examples/ when you want to: Prefer an example over a core package change when the external project is new, niche, or still proving community demand.
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The demo/ directory contains live demonstrations of AGT capabilities, including real-service walkthroughs and visual dashboards. Demos should help users see the system working end-to-end without changing the core product contract.
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The pipelines/ directory contains Azure DevOps release automation, especially ESRP-backed publishing flows for Python, npm, NuGet, Rust, and Go artifacts. - Treat every pipeline edit as security-sensitive. - Keep secrets, client IDs, key vault names, and certificate identifiers in pipeline secrets or variables, not inline in YAML. - Pin package-install commands to explicit versions where applicable. - Preserve least privilege and existing release gates. - Prefer comments that explain non-obvious ESRP or platform constraints.
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The policy decision runtime now ships from the registry as agent-control-spec, rebased on the agent-hooks control contract. This tree is what AGT layers on top of it. core/ is a deprecation shim that keeps the historical agent_control_specification_core symbols importable for one release cycle, and sdk/rust/ is AGT's host SDK. Read docs/acs-retarget.md before changing anything here. Use ACS terms when writing issues, docs, tests, and code comments. Do not introduce predecessor project concepts that ACS removed, and do not reintroduce the…
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This package is governed by an ultra-strict lint policy for generated code. All of the rules below are enabled to error in eslint.config.js via the shared local-node-rig/profiles/default/includes/eslint/flat/mixins/strict-codegen.js mixin. They apply…
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This package is governed by an ultra-strict lint policy for generated code. All of the rules below are enabled to error in eslint.config.js via the shared local-node-rig/profiles/default/includes/eslint/flat/mixins/strict-codegen.js mixin. They apply…
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This package is governed by an ultra-strict lint policy for generated code. All of the rules below are enabled to error in eslint.config.js via the shared local-node-rig/profiles/default/includes/eslint/flat/mixins/strict-codegen.js mixin. They apply…
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This package is governed by an ultra-strict lint policy for generated code. All of the rules below are enabled to error in eslint.config.js via the shared local-node-rig/profiles/default/includes/eslint/flat/mixins/strict-codegen.js mixin. They apply…
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Instructions for GitHub Copilot and other AI coding agents working with the Aspire repository. Aspire provides tools, templates, and packages for building observable, production-ready distributed applications. At its core is an app model that defines services, resources, and connections in a code-first approach. When authoring or reviewing a change, check test-selection impact if it: * Adds, removes, or renames a test project. * Adds or changes a CI job, reusable workflow, or run_* selection gate. * Adds or changes a…
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This is a Yarn v4 monorepo; packages live in packages/. All contributor knowledge lives in the wiki: If the wiki disagrees with this file, the wiki wins — open a…
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This is a Claude Agent SDK project, not an ADK one: app/agent.py declares root_agent (a ClaudeAgentOptions), app/app_utils/claude.py runs it, and app/fast_api_app.py serves it over A2A. Read .agents/skills/agents-cli-claude/SKILL.md before changing any of them. Experimental. Agent Runtime and Cloud Run are the supported targets. Models are Claude on Gemini platform: the model named in app/agent.py must be enabled in Model Garden for the project. agents-cli playground, eval dataset synthesize and eval optimize need ADK, so this project refuses them, as does publish…
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This is a LangChain project, not an ADK one: app/agent.py compiles a LangGraph graph and app/fast_api_app.py serves it over A2A. Read .agents/skills/agents-cli-langchain/SKILL.md before changing either. Experimental. Cloud Run and GKE are the supported targets. On Agent Runtime the container serves and traces normally, but everything that expects an ADK app is broken, because this project serves A2A and no reasoning_engine routes: - agents-cli publish gemini is refused: registration invokes the agent through :streamQuery. Publish from a Cloud Run or GKE…
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MicrosoftAGENTS.md
