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chore: rename project to DataFoundry
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.docs-internal/engineering/adr-0002-memory-authority-and-mastra-memory-boundary.md

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@@ -18,7 +18,7 @@ These mechanisms overlap. Without a clear authority model, the same fact can ent
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paths, for example through a metadata summary, Mastra WorkingMemory, long-term memory, and future observational memory.
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This would waste context budget, create inconsistent priority, and make audit/replay unclear.
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The project also has a stricter requirement than a generic chatbot memory layer: data-agent context must be scoped,
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The project also has a stricter requirement than a generic chatbot memory layer: data-foundry context must be scoped,
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auditable, and governed before it reaches the model. In particular, datasource-scoped memory must not leak across
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datasources, fresh SQL/tool evidence must outrank stale memory, and prompt-visible context must be explainable through
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`ContextPackage` / `ContextPromptView`.
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### 2. Long-Term Memory
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`metadata.long_term_memories` remains the authoritative long-term memory store for this data-agent system.
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`metadata.long_term_memories` remains the authoritative long-term memory store for this data-foundry system.
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Long-term memory records must preserve data-agent-specific governance fields:
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Long-term memory records must preserve data-foundry-specific governance fields:
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- `scope`: `user` / `session` / `datasource`;
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- `kind`: preference, constraint, dataset fact, analysis finding, decision, session state;
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### 4. Prompt Injection Ownership
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The model-visible prompt must be decided by the data-agent context compiler:
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The model-visible prompt must be decided by the data-foundry context compiler:
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```text
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logical sources
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- prompt-visible memory has a single governance path;
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- compact memory cannot silently duplicate through metadata and Mastra WorkingMemory;
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- Mastra-native features can still be used without surrendering data-agent audit boundaries;
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- Mastra-native features can still be used without surrendering data-foundry audit boundaries;
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- future Semantic Recall / OM can be evaluated safely in shadow mode.
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Negative:

.docs-internal/engineering/adr-0003-context-layering-and-naming.md

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@@ -137,7 +137,7 @@ Current migration:
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register built-in runtime sources.
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- New run-scoped sources that are not yet built in should enter through `additionalSources` on the source-layer
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runtime registry boundary, then through `additionalRuntimeSources` on the Mastra processor boundary. They must not
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require `createDataAgent()` to manually instantiate or register runtime sources.
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require `createDataFoundry()` to manually instantiate or register runtime sources.
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- Runtime source processors replace the current inventory snapshot for their registered `sourceType`s on every step,
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including when a source returns no items. Runtime sources are therefore fresh step-scoped projections, not append-only
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history; durable history must enter through memory/metadata repositories or explicit tool-history reference records.
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for message-id based rules such as `memory-summary:*` and `context:long-term-memory`.
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- The Mastra processor boundary is also the only production path that connects the source-layer runtime registry
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boundary to Mastra processors. This keeps long-term memory and WorkingMemory projection registration out of
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`createDataAgent()`.
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- `createDataAgent()` still creates the AG-UI event sink because AG-UI wrapping is a northbound protocol concern; the
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`createDataFoundry()`.
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- `createDataFoundry()` still creates the AG-UI event sink because AG-UI wrapping is a northbound protocol concern; the
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Mastra processor boundary consumes only the protocol-neutral `ContextProtocolEventSink`.
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Abstract base/interface:

.docs-internal/engineering/ag-ui-agent-runtime-architecture.puml

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@startuml
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title Data Agent - Current Runtime
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title DataFoundry - Current Runtime
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left to right direction
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skinparam componentStyle rectangle
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component "/api/v1/*\nConfig REST" as ConfigRest #FFFFFF
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component "ConfigApiRequest\nresources / jobs / artifacts" as ConfigApi #FFFFFF
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component "POST /api/copilotkit" as Endpoint #FFFFFF
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component "DataAgentAgUiAgent" as Bridge #FFFFFF
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component "DataFoundryAgUiAgent" as Bridge #FFFFFF
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component "Run Identity\nfingerprint / claim / replay" as Identity #F7C9B6
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component "TaskPlanProjector\ndynamic PLAN snapshot" as Plan #F7C9B6
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}
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package "Mastra Agent Runtime" #DCE8C9 {
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component "@ag-ui/mastra\nMastraAgent" as AgUiMastra
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component "Mastra DataAgent\nReAct + tool calling" as Agent
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component "Mastra DataFoundry\nReAct + tool calling" as Agent
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component "@ag-ui/mcp-middleware\nenabled MCP servers" as McpMiddleware
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component "MastraContextBudgetProcessor\nevery ReAct step" as ContextProcessor #F9D65C
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component "MastraTaskStateContextProcessor\nthread task snapshot" as TaskProcessor #F9D65C
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ConfigApi --> Gateway : datasource test / introspect
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ConfigApi --> Knowledge : KB upload / search / reindex
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ConfigApi --> Artifacts : detail / preview / download
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Endpoint --> Bridge : route dataAgent
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Endpoint --> Bridge : route dataFoundry
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Bridge --> Identity : threadId / runId / parentRunId
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Identity --> Metadata : find or atomic claim
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Identity --> Events : terminal duplicate replay

.docs-internal/engineering/ag-ui-agent-runtime-architecture.svg

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.docs-internal/engineering/agent-context-architecture.html

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<main class="shell">
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<header class="masthead">
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<div>
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<p class="kicker">Open Data Agent Workbench / R&amp;D B</p>
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<p class="kicker">DataFoundry Workbench / R&amp;D B</p>
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<h1>Context Control Room</h1>
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<p class="subtitle">一张图看清外部内容如何按五层上下文治理进入模型:Source、Inventory、Policy、Projection、Protocol。tool-observation 是 Source Layer 的工具结果子域,不是第六层。</p>
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</div>

.docs-internal/engineering/config-management-api.md

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@@ -414,7 +414,7 @@ MCP middleware 不能成为模型上下文和安全策略的旁路:
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3. 根据已缓存 manifest 为每个解析后的 MCP tool 注册独立 `ToolObservationAdapter`;可以共享
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参数化 `McpToolObservationAdapter` 类,但 registry 中仍是一工具一 adapter 实例。
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4. middleware 挂在 run 内创建的 `MastraAgent` 上,而不是包裹最外层
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`DataAgentAgUiAgent`。这样它生成的 continuation 不会重复进入 run claim,所有标准
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`DataFoundryAgUiAgent`。这样它生成的 continuation 不会重复进入 run claim,所有标准
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`TOOL_CALL_RESULT` 也继续经过现有 `emit -> RunEventWriter -> subscriber` 北向链路。
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5. middleware 把 MCP observation 追加到下一轮 messages 后,现有 Mastra
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`MastraContextBudgetProcessor.processInputStep``MastraToolObservationRouter` 在每一步将结果路由到
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"enabledKnowledgeIds": [],
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"enabledMcpServerIds": ["notion"],
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"activeLlmProfileId": "qwen-plus-default",
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"activeSkillId": "data-agent-default"
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"activeSkillId": "data-foundry-default"
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}
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}
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```
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"enabledDatasourceIds": ["sales-prod-readonly"],
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"enabledKnowledgeIds": [],
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"enabledMcpServerIds": ["notion"],
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"enabledSkillIds": ["data-agent-default", "schema-explore"],
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"enabledSkillIds": ["data-foundry-default", "schema-explore"],
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"fileIds": ["file-ref-1"],
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"activeDatasourceId": "sales-prod-readonly",
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"activeLlmProfileId": "qwen-plus-default",

.docs-internal/engineering/context-governance-pipeline.mmd

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subgraph API["agent-runtime Package Boundary"]
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PUBLIC["index.ts<br/>public app API"]
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TESTING["testing.ts<br/>smoke-only internal seams"]
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AGENT["createDataAgent<br/>tool + context boundary assembly"]
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AGENT["createDataFoundry<br/>tool + context boundary assembly"]
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end
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subgraph SOURCE["1. Source Layer<br/>runtime sources + tool observation subdomain"]

.docs-internal/engineering/context-governance-pipeline.svg

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.docs-internal/engineering/conversation-memory-architecture.puml

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actor "CopilotKit / AG-UI\nClient" as Client
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package "apps/api" #E0F2FE {
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component "DataAgentAgUiAgent" as Api
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component "DataFoundryAgUiAgent" as Api
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component "ConversationMemory\nService" as MemoryService
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component "Window Policy\nToken + Char Budget" as WindowPolicy
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component "ConversationMemory\nEventObserver" as Observer
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}
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package "packages/agent-runtime" #FEF3C7 {
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component "createDataAgent" as Factory
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component "createDataFoundry" as Factory
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component "MastraContextBudgetProcessor" as Budget
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component "MastraTaskStateContextProcessor" as TaskState
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component "Mastra DataAgent\nReAct + tools" as Agent
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component "Mastra DataFoundry\nReAct + tools" as Agent
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}
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package "Mastra / AG-UI" #FCE7F3 {

.docs-internal/engineering/conversation-memory-architecture.svg

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