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Sprint Execution Coordinator

Overview and Role in the Factory

The SprintExecutionCoordinator is a core orchestrator in the ConnectSoft AI Software Factory. It is responsible for managing the lifecycle of sprints, ensuring that feature execution is scoped, traceable, and milestone-aligned.

It orchestrates agents such as the ProductOwnerAgent, BackendDeveloperAgent, TestGeneratorAgent, QAAgent, and DevOpsAgent β€” but only within the context of an active sprint. Its design enforces execution windows, gate-based progression, and trace-linked output verification.

In the ConnectSoft Factory, a sprint is not a date range β€” it’s a controlled execution boundary, defined by traceable artifacts and driven by logical FSM transitions.


🎯 Core Purpose

  • Enforce scoped execution of features and agents during a sprint
  • Emit lifecycle events: SprintPlanned, SprintStarted, SprintCheckpoint, SprintClosed
  • Ensure only agents tagged to the current sprint are activated
  • Link all generated artifacts (code, tests, metrics) to a sprint_id and trace_id
  • Track progress and gate transitions against milestone_id targets

πŸ“¦ Key Capabilities

Capability Description
Sprint Lifecycle FSM Defines logical states: Planned, Active, Checkpoint, Closed, Blocked
Agent Activation Filter Activates only agents associated with features in current sprint
Trace Injection Ensures all artifacts and metrics include sprint_id, milestone_id, and trace_id
Gate Enforcement Blocks SprintClosed until required outputs (e.g., tests, PRs, CI runs) are complete
Retry and Resume Supports PlanningResumed, partial reruns, and failure correction flows

🧬 Sprint Metadata Structure

{
  "sprint_id": "sprint-2025-05-MVP1",
  "milestone_id": "mvp-core",
  "features": ["BookingFlow", "Notification.Email.Send"],
  "agents": ["ProductOwnerAgent", "BackendDeveloperAgent", "TestGeneratorAgent"],
  "status": "Planned",
  "trace_id": "trace-abc123"
}
````

---

### 🧠 Why This Coordinator Matters

Without the `SprintExecutionCoordinator`, the factory would risk:

* Unscoped agent activation
* Feature execution without QA enforcement
* Milestone advancement without artifact validation
* Lack of sprint-aware dashboards or Studio visualization
* Poor traceability across thousands of services

It serves as the **governor and scheduler** of AI execution cycles, balancing speed with structure.

---

## Position in the Execution Flow

The `SprintExecutionCoordinator` operates in the **middle phase of the Factory lifecycle**, directly after milestone planning and before CI/CD orchestration. It is triggered when:

- A milestone becomes **ready for execution**
- A `SprintPlanned` event is emitted by the `ProductOwnerAgent` or `MilestoneLifecycleCoordinator`

It marks the beginning of a **bounded, traceable execution window**, during which features are implemented, validated, and linked to milestone goals.

---

### πŸ” Execution Phase

| Phase              | Position |
|--------------------|----------|
| **Project Initialization** | ❌ Before |
| **Milestone Planning**     | βœ… Precursor |
| **Sprint Execution**       | βœ… Active Phase |
| **CI/CD & Deployment**     | πŸ”„ Triggered After |
| **Release Management**     | ❌ Follows Output |

---

### πŸ“Œ Dependencies

| Upstream Coordinators/Agents      | Required Outputs |
|----------------------------------|------------------|
| `ProjectBootstrapOrchestrator`    | `DevOpsArtifactsReady` |
| `MilestoneLifecycleCoordinator`   | `MilestoneReadyForExecution`, `MilestoneScopeLocked` |
| `ProductOwnerAgent`               | `SprintPlanned`, `sprint-definition.json` |

---

### πŸš€ What It Unlocks

Once the `SprintExecutionCoordinator` is triggered, it enables:

- Activation of scoped AI agents (execution is no longer global)
- Generation of trace-linked artifacts (code, tests, diagrams)
- Emission of `SprintStarted`, `SprintCheckpoint`, and `SprintClosed` events
- Enforcement of milestone gates via `sprint-trace-matrix.json`
- Integration with CI/CD pipeline emitters and QA validation routines

---

### 🧬 Execution Timeline Diagram

```mermaid
flowchart TD
    MilestonePlanning -->|SprintPlanned| SprintExecutionCoordinator
    SprintExecutionCoordinator --> AgentCluster
    AgentCluster -->|ArtifactReady| SprintExecutionCoordinator
    SprintExecutionCoordinator -->|SprintClosed| MilestoneLifecycleCoordinator
    SprintExecutionCoordinator -->|ArtifactsTagged| CI/CD Orchestrators
````

---

### 🧠 Summary

The `SprintExecutionCoordinator` serves as the **execution gateway between planning and delivery** β€” ensuring that all actions performed during a sprint are:

* βœ… Scoped
* βœ… Traceable
* βœ… Testable
* βœ… Governed

---

## Responsibilities

The `SprintExecutionCoordinator` is responsible for managing the **entire lifecycle of a sprint**, ensuring that agents operate only within the authorized scope and that all outputs are trace-linked, quality-checked, and milestone-aligned.

It acts as a **gatekeeper, scheduler, and validator** for sprint execution, providing both structure and resilience for fast-paced, multi-agent orchestration.

---

### βœ… Core Responsibilities

| Responsibility | Description |
|----------------|-------------|
| **Activate Sprint** | React to `SprintPlanned` event and transition sprint to `Active` state |
| **Enable Agents by Scope** | Only activate agents for features explicitly assigned to the current sprint |
| **Manage Sprint FSM** | Handle state transitions (`Planned β†’ Active β†’ Checkpoint β†’ Closed`) |
| **Track Progress** | Monitor agent activity, artifact readiness, and test pass status |
| **Emit Lifecycle Events** | `SprintStarted`, `SprintCheckpoint`, `SprintClosed`, `SprintBlocked` |
| **Enforce Completion Gates** | Validate `sprint-trace-matrix.json` against expected features and tests |
| **Support Recovery and Retry** | Allow safe re-execution or continuation after failure (`SprintResumed`, `RetrySprintExecution`) |

---

### πŸ“¦ Additional Outputs Controlled

- `SprintStartedEvent` β€” activates agents and enables log traces
- `sprint-trace-matrix.json` β€” artifact-to-feature map
- `qa-validation-report.md` β€” optional, links QA status per feature
- `SprintClosedEvent` β€” unlocks CI/CD and milestone transitions

---

### 🧠 Sprint FSM States (Internal)

| State         | Description |
|---------------|-------------|
| `Planned`      | Sprint has been scoped and planned but not yet active |
| `Active`       | Agents are currently working; outputs are being generated |
| `Checkpoint`   | Optional mid-sprint pause to validate progress or perform manual review |
| `Blocked`      | Execution halted due to failure, missing artifact, or unmet gate |
| `Closed`       | Sprint successfully completed and outputs validated |

---

### πŸ” Coordinated Domains

| Domain | Coordination Role |
|--------|-------------------|
| **Features** | Assign agents and track story delivery |
| **Tests**    | Link generated tests to feature IDs and verify pass rate |
| **CI/CD**    | Prepare tagging and artifact linkage based on sprint completion |
| **Security** | Validate that generated code includes tracing, auth policies, and observability hooks |

---

### 🧩 Related Coordinators It Interacts With

- `MilestoneLifecycleCoordinator` (for milestone advancement)
- `CI/CD ArtifactCoordinator` (for version tagging and deployment triggers)
- `QAOrchestrator` (for test coverage enforcement)

---

### 🎯 Summary

The `SprintExecutionCoordinator` is the **central timing and scope enforcement unit** in the Factory’s orchestration layer.  
It ensures that **everything generated during a sprint is intentional, traceable, and governed**.

---

## Triggering Events

The `SprintExecutionCoordinator` is fully **event-driven**, activated by upstream planning components and controlling downstream agent execution and milestone progression through structured lifecycle events.

It listens for well-defined events to begin execution and emits events to signal sprint state changes, progress checkpoints, and completion status.

---

### 🚦 Primary Triggering Events

| Event               | Emitted By                  | Description |
|---------------------|-----------------------------|-------------|
| `SprintPlanned`      | `ProductOwnerAgent` or `MilestoneLifecycleCoordinator` | Indicates that sprint scope, agents, and features are defined. Triggers coordinator startup. |
| `PlanningResumed`    | Manual or automatic resume | Re-initializes a previously paused or blocked sprint. May include additional features or agent instructions. |
| `RetrySprintExecution` | Factory FSM or Studio UI | Used to restart execution flow after partial or failed sprint attempt. |

---

### πŸ” Re-Entry / Update Events

| Event                | Description |
|----------------------|-------------|
| `SprintCheckpointRequested` | Triggers a pause to inspect progress before sprint closure. |
| `SprintExtended`     | Updates current sprint to include new features or scope (e.g., after blueprint update). |
| `SprintBlocked`      | Internal state β€” signals unmet gate condition (e.g., missing artifacts, failed QA). |

---

### πŸ“€ Events Emitted by the Coordinator

| Event               | Triggered When |
|---------------------|----------------|
| `SprintStarted`      | Sprint scope is loaded and agent activation begins. |
| `SprintCheckpoint`   | Mid-sprint progress inspection triggered. |
| `SprintClosed`       | All artifacts validated, test coverage met, CI/CD ready. |
| `SprintFailed`       | Sprint terminated due to critical blocking failure. |
| `SprintEscalated`    | Human intervention requested (e.g., QA rejection, scope misalignment). |

---

### 🧠 Event Payload Structure: `SprintStarted`

```json
{
  "event": "SprintStarted",
  "sprint_id": "sprint-2025-06-notification",
  "milestone_id": "mvp-ready",
  "trace_id": "trace-xyz789",
  "features": ["SendEmail", "ScheduleRetry"],
  "agents": ["BackendDeveloperAgent", "TestGeneratorAgent", "QAAgent"],
  "status": "Active",
  "started_at": "2025-05-13T08:00:00Z"
}
````

This event is consumed by:

* Activated agents (to determine their scope)
* Studio for real-time visualization
* Observability dashboards
* Milestone FSM controllers

---

### πŸ“‘ Observability Integration

All events include:

* `trace_id`
* `sprint_id`
* `milestone_id`
* `agent_roles`
* Timestamps (`started_at`, `completed_at`)
* `status`

β†’ Enables fine-grained time-to-execute metrics, agent success rates, and traceback across CI/CD.

---

### βœ… Summary

The `SprintExecutionCoordinator` is **fully reactive**, responding to factory planning decisions and emitting structured events to:

* Activate execution
* Gate milestone progression
* Enable traceable delivery
* Trigger downstream automation

---

## Inputs

The `SprintExecutionCoordinator` requires a structured set of inputs to launch, monitor, and complete a sprint. These inputs define what should be executed, by whom, and under which milestone and trace context.

Inputs are derived from upstream planning events and artifacts, especially those emitted by the `ProductOwnerAgent`, `MilestoneLifecycleCoordinator`, and Studio interface.

---

### πŸ“₯ Required Inputs

| Input                     | Type     | Description |
|---------------------------|----------|-------------|
| `sprint_id`              | string   | Unique identifier for the sprint (e.g., `sprint-2025-06-MVP2`) |
| `milestone_id`           | string   | Milestone this sprint contributes to (e.g., `mvp-ready`) |
| `features[]`             | string[] | List of feature IDs assigned to the sprint (e.g., `BookingFlow`, `SendNotification`) |
| `agents[]`               | string[] | Agent types expected to be active during the sprint (e.g., `TestGeneratorAgent`, `BackendDeveloperAgent`) |
| `trace_id`               | string   | Execution trace anchor used for observability and artifact correlation |
| `scope_definition_file`  | file     | File or pointer to the sprint plan (`sprint-definition.json`) containing scope metadata |
| `execution_window`       | object   | Optional logical timing constraints (e.g., max retries, max duration, checkpoint frequency) |

---

### 🧬 `sprint-definition.json` Sample

```json
{
  "sprint_id": "sprint-2025-06-MVP2",
  "milestone_id": "mvp-ready",
  "features": [
    { "id": "BookingFlow", "priority": "P1", "estimation": 5 },
    { "id": "SendConfirmationEmail", "priority": "P2", "estimation": 3 }
  ],
  "agents": [
    "BackendDeveloperAgent",
    "TestGeneratorAgent",
    "QAAgent"
  ],
  "trace_id": "trace-abc-123",
  "checkpoints": 1,
  "retryPolicy": { "maxAttempts": 2 }
}
````

This document is validated on startup and persisted alongside trace metadata for auditability.

---

### πŸ” Optional / Contextual Inputs

| Input                   | Type    | Description                                                          |
| ----------------------- | ------- | -------------------------------------------------------------------- |
| `manual_override`       | boolean | Allows sprint execution to proceed even if some gates are unmet      |
| `resumption_context`    | object  | Used if sprint is resuming from a paused or checkpointed state       |
| `security_profile`      | object  | Indicates if any endpoint/auth observability is required by agents   |
| `testCoverageThreshold` | number  | Required percent test coverage (e.g., `85`) enforced at sprint close |

---

### 🧠 Configuration Source Options

These inputs can be injected via:

* `SprintPlanned` event payload
* Files in the planning workspace (`/planning/sprint-definition.json`)
* Studio UI input (via sprint planning dashboard)
* `SprintResumed` or `SprintRetry` payloads

---

### βœ… Summary

The `SprintExecutionCoordinator` requires:

* A **clearly scoped sprint plan**
* A **list of features and agents**
* A **trace ID** for audit and observability
* Optional execution controls (duration, retries, checkpoints)

These inputs enable the coordinator to run a **fully traceable, scoped, and validated execution window** aligned to sprint goals and milestone gates.

---

## Outputs

The `SprintExecutionCoordinator` produces a set of traceable, event-driven outputs that represent the state, results, and compliance of a sprint. These outputs serve as:

- Activation signals for downstream agents
- Gate triggers for milestones and deployments
- Observability inputs for dashboards and auditors
- Artifacts consumed by QA and CI/CD components

---

### πŸ“€ Primary Outputs

| Output                       | Type     | Description |
|------------------------------|----------|-------------|
| `SprintStarted`              | Event    | Indicates sprint has begun and agent execution is permitted |
| `SprintCheckpoint`           | Event    | Optional progress checkpoint for QA and trace analysis |
| `SprintClosed`               | Event    | Signals all execution and validation steps for this sprint are complete |
| `SprintFailed`               | Event    | Indicates a blocking issue or unmet gate prevented sprint closure |
| `SprintEscalated`            | Event    | Sent if manual intervention is required (e.g., failed validation) |
| `sprint-trace-matrix.json`   | Artifact | JSON artifact linking features, agents, artifacts, tests, and trace IDs |
| `qa-validation-report.md`    | Artifact | Optional summary of test coverage and QA metrics per feature |
| `execution-metadata.json[]`  | Artifact | Agent-generated trace files during sprint execution |

---

### πŸ“˜ `sprint-trace-matrix.json` Example

```json
{
  "sprint_id": "sprint-2025-06-MVP2",
  "milestone_id": "mvp-ready",
  "trace_id": "trace-abc-123",
  "features": [
    {
      "id": "BookingFlow",
      "artifacts": ["BookingHandler.cs", "booking-api.feature"],
      "tests": ["BookingFlowTests.cs"],
      "agent": "BackendDeveloperAgent",
      "status": "complete"
    }
  ],
  "coverage": "92%"
}
````

βœ… This artifact is required to pass milestone gate checks and close the sprint.

---

### πŸ“¦ File Output Paths

| File                       | Location                             |
| -------------------------- | ------------------------------------ |
| `sprint-trace-matrix.json` | `/execution/sprints/{sprint_id}/`    |
| `qa-validation-report.md`  | `/execution/sprints/{sprint_id}/qa/` |
| `execution-metadata.json`  | One per agent β†’ `/execution/agents/` |

---

### 🧠 Event Payload: `SprintClosed`

```json
{
  "event": "SprintClosed",
  "sprint_id": "sprint-2025-06-MVP2",
  "milestone_id": "mvp-ready",
  "trace_id": "trace-abc-123",
  "status": "complete",
  "artifacts_validated": true,
  "coverage": "92%",
  "timestamp": "2025-05-13T16:32:00Z"
}

This output is consumed by:

  • MilestoneLifecycleCoordinator
  • PipelineGenerator
  • Studio Sprint Tracker
  • CI/CD Tagging System

πŸ“Š Observability Metrics Emitted

Metric Description
sprint_execution_duration_ms Time from SprintStarted to SprintClosed
sprint_feature_completion_rate % of scoped features completed
sprint_test_coverage_percent Final test coverage from QA report
agent_execution_success_rate Agent success/failure ratio during sprint

βœ… Summary

The SprintExecutionCoordinator produces:

  • Structured events to track sprint state
  • Artifact matrices for traceability and QA
  • Metrics and logs for audit, observability, and milestone promotion

These outputs make every sprint measurable, auditable, and automatically promotable.


Collaborating Agents

The SprintExecutionCoordinator serves as the execution gateway for a select group of AI agents during each sprint. It activates, supervises, and validates their contributions within a clearly scoped window of time and trace.

These agents are chosen based on the sprint plan and are limited to executing within the assigned sprint_id, milestone_id, and feature_id[] context.


πŸ€– Core Collaborating Agents

Agent Role in Sprint
ProductOwnerAgent Finalizes sprint plan, monitors backlog shifts, emits checkpoints
BackendDeveloperAgent Implements service logic, commands, and use case handlers
TestGeneratorAgent Generates SpecFlow, BDD, and unit tests for each feature
QAAgent Validates trace-test linkage, executes test cases, enforces coverage gates
DevOpsAgent Applies CI/CD pipeline updates or release plan tags (post-sprint)
GitCommitAgent Commits all sprint-generated artifacts to their respective Git repositories

πŸ” Agent Activation Flow

  1. SprintExecutionCoordinator receives SprintPlanned
  2. Loads allowed agents[] and features[] for the sprint
  3. For each feature:
    • Activates the corresponding agent with feature + trace context
    • Tracks ArtifactReady and AgentExecutionCompleted events
    • Collects execution-metadata.json from each agent
  4. QAAgent and DevOpsAgent are activated after all other agents complete their traceable steps.

🧠 Agent Execution Context Injected

Each agent receives:

{
  "sprint_id": "sprint-2025-06-MVP2",
  "milestone_id": "mvp-ready",
  "trace_id": "trace-abc-123",
  "feature_id": "BookingFlow",
  "agent_role": "BackendDeveloperAgent",
  "allowed_skills": ["GenerateHandler", "EmitCommand", "PushCode"]
}
````

βœ… Ensures agents **cannot operate outside** of their assigned feature and sprint scope.

---

### πŸ“Ž Optional/Conditional Agents

| Agent                         | Activation Criteria                                           |
| ----------------------------- | ------------------------------------------------------------- |
| `FeatureToggleInjectionAgent` | Only if `featureFlags[]` present in sprint plan               |
| `SecurityEngineerAgent`       | Enabled for regulated sprints or security milestone alignment |
| `ObservabilityAgent`          | Injects OpenTelemetry hooks based on trace config             |
| `HumanApprovalEscalator`      | Triggered only if `SprintEscalated` event is emitted          |

---

### 🧩 Agent Interaction Model

```mermaid
sequenceDiagram
  SprintCoordinator->>BackendDev: Execute BookingFlow
  SprintCoordinator->>TestGenerator: Create tests for BookingFlow
  SprintCoordinator->>QAAgent: Validate artifacts and coverage
  SprintCoordinator->>DevOpsAgent: Inject pipeline tags
  SprintCoordinator->>GitAgent: Commit artifacts to repo

Each agent emits trace-tagged events that SprintExecutionCoordinator collects to verify sprint completion.


βœ… Summary

The SprintExecutionCoordinator orchestrates only the agents needed for the sprint’s scope, tracks their outputs, and validates their contributions.

This scoped agent activation model enables:

  • High concurrency
  • Governance per sprint
  • Traceable execution per artifact

System Prompt

The SprintExecutionCoordinator constructs and dispatches structured prompts to activate agents within the current sprint context. These prompts include sprint-level metadata, assigned feature scope, traceability anchors, and skill constraints β€” ensuring agents behave deterministically and securely within sprint boundaries.

Each prompt is agent-type specific, but always includes the sprint scope and trace envelope.


🧠 Example System Prompt (Generic Template)

You are the {{agent_role}} participating in a sprint inside the ConnectSoft AI Software Factory.

Your current sprint context is:

- sprint_id: {{sprint_id}}
- milestone_id: {{milestone_id}}
- trace_id: {{trace_id}}
- feature_id: {{feature_id}}
- runtime_environment: {{environment}}

Your responsibilities are:

- Execute only tasks defined for your agent type
- Ensure all outputs are trace-tagged with `sprint_id` and `trace_id`
- Do not operate outside your assigned `feature_id`
- Emit all results in structured form (file, event, or trace log)

You may use the following skills:
{{allowed_skills}}

Respond with:
{
  "agent_role": "...",
  "feature_id": "...",
  "files_emitted": [...],
  "status": "completed",
  "trace_id": "...",
  "duration_ms": ...
}
````

---

### πŸ”§ Dynamic Prompt Variables

| Placeholder          | Description                                 |
| -------------------- | ------------------------------------------- |
| `{{agent_role}}`     | Agent type (e.g., `TestGeneratorAgent`)     |
| `{{sprint_id}}`      | Sprint this agent is operating under        |
| `{{milestone_id}}`   | Associated milestone for trace validation   |
| `{{trace_id}}`       | Root trace for observability correlation    |
| `{{feature_id}}`     | Single feature the agent is responsible for |
| `{{environment}}`    | Current runtime tier (`dev`, `test`, etc.)  |
| `{{allowed_skills}}` | Specific skills enabled for the agent       |

---

### πŸ“¦ Example Prompt (for `TestGeneratorAgent`)

```text
You are the TestGeneratorAgent assigned to sprint `sprint-2025-06-MVP2`.

Feature: `BookingFlow`
Trace ID: `trace-abc123`
Milestone: `mvp-ready`

Use your BDD and SpecFlow generation skills to create:

- 1 feature file (`BookingFlow.feature`)
- 1 unit test class (`BookingFlowTests.cs`)

Tag all outputs with trace metadata and respond with file paths.

🧠 Prompt Delivery Methods

  • Inline Semantic Kernel plugin invocations
  • Azure Function trigger calls
  • Remote task queue (via Event Grid or Azure Service Bus)
  • Studio β€œManual Agent Re-Activation” interface

βœ… Summary

System prompts dispatched by the SprintExecutionCoordinator ensure:

  • Agents operate only within sprint boundaries
  • Outputs are traceable and auditable
  • Prompt behavior is role-specific and policy-compliant

This prompt model enables safe, autonomous, scoped execution per sprint-feature-agent combination.


Execution Flow (Steps)

The SprintExecutionCoordinator follows a well-defined, stateful execution process. This flow governs how the sprint begins, activates agents, tracks progress, validates outputs, and emits terminal events.

Each step is event-driven, traceable, and scoped to the active sprint and milestone context.


πŸ” Step-by-Step Execution Flow

1. Wait for SprintPlanned Event

  • Load sprint_id, milestone_id, features[], agents[], and trace_id
  • Validate sprint-definition.json exists and passes schema checks

2. Initialize Execution Context

  • Inject trace and sprint metadata into observability layer
  • Persist sprint metadata to /execution/sprints/{sprint_id}/sprint-context.json
  • Transition FSM state to Planned β†’ Active

3. Activate Agents by Feature

For each feature_id: - Activate corresponding agents from the agents[] list - Inject system prompt and execution scope - Monitor emitted events: ArtifactReady, SkillExecutionCompleted

4. Track Agent Outputs

  • Collect execution-metadata.json per agent
  • Build sprint-trace-matrix.json incrementally
  • If enabled: perform mid-sprint checkpoint (SprintCheckpoint)

5. Validate Completion Conditions

  • Confirm each feature_id has:
    • At least one code artifact (ArtifactReady)
    • At least one test case or coverage report (qa-validation-report.md)
  • Confirm test coverage meets threshold if defined
  • Validate trace metadata integrity

6. Emit SprintClosed

  • Persist final sprint-trace-matrix.json
  • Emit SprintClosed event with validation summary
  • Update observability spans with duration, status, and metrics

7. Forward Control to MilestoneCoordinator / CI/CD

  • Trigger MilestoneLifecycleCoordinator to evaluate milestone gates
  • Trigger PipelineGenerator to begin artifact tagging or release promotion

πŸ“‚ Generated Artifacts

Artifact Created At Step
sprint-context.json Step 2
execution-metadata.json[] Step 4
sprint-trace-matrix.json Step 5
qa-validation-report.md Step 5
SprintClosed event Step 6

🧠 FSM Transitions (Logical)

From β†’ To Trigger
Planned β†’ Active SprintPlanned validated
Active β†’ Checkpoint Progress threshold met
Active β†’ Blocked Failed validation / missing artifact
Active β†’ Closed All completion conditions met

βœ… Summary

This execution process ensures that every sprint is:

  • Trace-anchored
  • Feature-scoped
  • Agent-driven
  • Artifact-verified

…and ends only when traceable, testable, CI/CD-ready output exists.


Execution Flow (Diagram)

The following Mermaid sequenceDiagram illustrates the runtime flow of sprint execution, showing how the SprintExecutionCoordinator interacts with upstream planners, downstream validators, and per-sprint agents.

This diagram emphasizes trace propagation, FSM transitions, and coordinated agent activation across a defined sprint boundary.


🧬 Mermaid Diagram: Sprint Execution Lifecycle

sequenceDiagram
    participant Planner as ProductOwnerAgent
    participant Coordinator as SprintExecutionCoordinator
    participant Agent1 as BackendDeveloperAgent
    participant Agent2 as TestGeneratorAgent
    participant QA as QAAgent
    participant DevOps as DevOpsAgent
    participant Milestone as MilestoneLifecycleCoordinator

    Planner->>Coordinator: Emit SprintPlanned
    Coordinator->>Coordinator: Validate sprint-definition.json
    Coordinator->>Coordinator: Transition to Active
    Coordinator->>Agent1: Execute BookingFlow
    Coordinator->>Agent2: Generate BookingFlow Tests
    Agent1-->>Coordinator: Emit ArtifactReady
    Agent2-->>Coordinator: Emit TestCasesGenerated
    Coordinator->>QA: Validate coverage, trace links
    QA-->>Coordinator: Emit QAValidationReport
    Coordinator->>DevOps: Tag CI pipeline, inject sprint metadata
    DevOps-->>Coordinator: Confirm CI Ready
    Coordinator->>Coordinator: Validate trace matrix
    Coordinator-->>Milestone: Emit SprintClosed
````

---

### 🧠 Key Execution Highlights

| Phase                      | Description                                                                            |
| -------------------------- | -------------------------------------------------------------------------------------- |
| **Activation**             | Coordinator receives `SprintPlanned`, validates scope, and transitions FSM to `Active` |
| **Scoped Agent Execution** | Agents only act on their assigned `feature_id`, using injected system prompts          |
| **Observability**          | Every interaction is trace-tagged (`sprint_id`, `trace_id`, `milestone_id`)            |
| **QA Enforcement**         | QAAgent validates artifact-to-feature mappings and test thresholds                     |
| **Completion**             | Once validated, `SprintClosed` is emitted and `sprint-trace-matrix.json` is finalized  |

---

### 🧩 FSM Path Summary

```mermaid
stateDiagram-v2
    [*] --> Planned
    Planned --> Active: SprintPlanned
    Active --> Checkpoint: MidSprintReview
    Active --> Blocked: MissingArtifact
    Active --> Closed: AllConditionsMet
    Blocked --> Active: PlanningResumed
    Closed --> [*]
Hold "Alt" / "Option" to enable pan & zoom

βœ… Summary

This flow and diagram provide a visual representation of how the SprintExecutionCoordinator:

  • Activates only the necessary agents
  • Enforces trace-linked execution
  • Ensures QA coverage and trace matrix completeness
  • Interfaces with CI/CD and milestone governance

Required Blueprints and Artifacts

The SprintExecutionCoordinator operates based on a set of structured, declarative blueprints and configuration files. These inputs define the sprint’s scope, traceability anchors, execution constraints, and success criteria.

By formalizing these artifacts, the Factory ensures repeatable, auditable, and governable sprint execution cycles.


πŸ“˜ Required Blueprints

Artifact Description
sprint-definition.json Core sprint execution plan: defines sprint_id, milestone_id, features, agents, trace_id, execution rules
features.yaml Contains definitions for all blueprint-derived features, including priorities, dependencies, and agents assigned
milestones.yaml Maps each milestone to expected features and sprint(s), used to gate sprint closure and milestone progression
execution-timeline.mmd Optional visual timeline of planned sprint phases (used in Studio dashboards)

πŸ“‚ Example: sprint-definition.json

{
  "sprint_id": "sprint-2025-07-userauth",
  "milestone_id": "auth-stable-v1",
  "trace_id": "trace-7482bfa3",
  "features": [
    "LoginHandler",
    "TokenValidation",
    "UserProfileQuery"
  ],
  "agents": [
    "BackendDeveloperAgent",
    "TestGeneratorAgent",
    "QAAgent"
  ],
  "checkpoints": 1,
  "testCoverageThreshold": 90
}
````

---

### πŸ“‚ Example: `features.yaml`

```yaml
features:
  - id: LoginHandler
    assignedSprint: sprint-2025-07-userauth
    priority: P1
    requiredBy: milestone:auth-stable-v1
    agents:
      - BackendDeveloperAgent
      - TestGeneratorAgent
  - id: TokenValidation
    assignedSprint: sprint-2025-07-userauth
    priority: P1
    requires: [LoginHandler]
    agents: [BackendDeveloperAgent]

πŸ“¦ Resolved Inputs (During Startup)

Artifact / Field Purpose
trace_id Injected into all events, logs, commits
sprint_id Used in all prompt injections and logs
feature_id[] Drives agent activation map
milestone_id Used for gate checks at close
testCoverageThreshold Enforced before emitting SprintClosed
allowed_agents[] Whitelist for which agents may run during sprint

πŸ” Observability Integration Files

  • sprint-context.json β€” context snapshot of all sprint metadata
  • execution-metadata.json[] β€” per-agent records of file generation, success/failure
  • sprint-trace-matrix.json β€” feature-to-artifact validation report
  • qa-validation-report.md β€” optional, for manual milestone review

βœ… Summary

The SprintExecutionCoordinator requires and consumes:

  • Structured sprint blueprints
  • Fully traceable feature plans
  • Milestone-aligned scoping rules
  • Agent-bound execution constraints

These artifacts ensure the Factory executes sprints safely, consistently, and transparently across thousands of services.


AI Skills and Plugins Used

The SprintExecutionCoordinator uses Semantic Kernel skills and plugins to activate agents, orchestrate their behavior, enforce scope constraints, and track outputs. It does not generate content itself β€” instead, it delegates responsibilities to trace-aware agents configured for the current sprint.

These skills allow the coordinator to operate in a modular, policy-compliant, and parallelized manner.


🧠 Core Semantic Skills Utilized

Skill / Plugin Purpose
AgentActivationSkill.ActivateByScope Activates a specific agent with trace + sprint scope
TraceabilitySkill.InjectSprintTrace Adds trace_id, sprint_id, milestone_id into logs, commits, events
ValidationSkill.CheckAgentOutput Confirms agent outputs meet expected test or coverage thresholds
QAValidationSkill.CompileTraceMatrix Builds the sprint-trace-matrix.json from agent outputs
StateMachineSkill.AdvanceSprintState Transitions internal FSM between sprint states
CheckpointSkill.EmitMidSprintReview Emits a checkpoint summary for Studio or agents

πŸ“˜ Example: Agent Activation Skill Call

{
  "agent": "TestGeneratorAgent",
  "feature_id": "LoginHandler",
  "trace_id": "trace-7482bfa3",
  "sprint_id": "sprint-2025-07-userauth",
  "milestone_id": "auth-stable-v1",
  "skills_allowed": ["GenerateSpecFlow", "EmitTestClass"]
}
````

This is sent to the `AgentActivationSkill`, which prepares the system prompt, routes the call to the selected AI agent, and logs the result for post-sprint analysis.

---

### 🧩 Optional / Conditional Skills

| Skill / Plugin                       | Trigger                                                |
| ------------------------------------ | ------------------------------------------------------ |
| `FeatureToggleSkill.InjectFlags`     | If `featureFlags[]` is defined in sprint               |
| `EditionSkill.OverrideAgentBehavior` | If the sprint is part of an edition-specific milestone |
| `ObservabilitySkill.InjectSpans`     | If OpenTelemetry is enabled in project config          |
| `SecuritySkill.AnnotateTraceSpan`    | If security policy integration is enabled              |

---

### πŸ”§ Plugin Execution Context

* All plugins receive:

  * `trace_id`
  * `sprint_id`
  * `milestone_id`
  * `feature_id`
  * `agent_role`
  * Execution parameters (e.g., skills allowed, coverage gates)

* All responses are logged in:

  * `execution-metadata.json`
  * `sprint-trace-matrix.json`

---

### πŸ“¦ Plugin Source and Extensibility

| Plugin Type                    | Hosted By                                           | Scope                                              |
| ------------------------------ | --------------------------------------------------- | -------------------------------------------------- |
| Semantic Kernel Plugins        | AI Orchestration Layer                              | Agent activation, trace injection, skill filtering |
| Azure Functions                | For durable state machines or skill expansion       |                                                    |
| Local Plugins (if self-hosted) | Custom sprint-specific CI/CD or QA validation logic |                                                    |

---

### βœ… Summary

The `SprintExecutionCoordinator` doesn’t write code β€” it **activates and governs the agents that do**.

Through use of AI plugins and skills, it enables:

* Controlled, repeatable, parallel agent execution
* Sprint-bounded trace injection
* Observability-compliant behavior across roles

---

## Human Intervention Hooks

While the `SprintExecutionCoordinator` is designed to operate autonomously, there are strategic points in the sprint lifecycle where **manual approval, override, or escalation** may be necessary.

These hooks allow the Factory to **pause, review, or adjust** sprint execution in response to failures, policy gates, or incomplete agent outputs β€” without compromising traceability or consistency.

---

### πŸ§‘β€πŸ’Ό Manual Review Scenarios

| Hook Point                 | Description |
|----------------------------|-------------|
| `SprintApprovalRequired`   | Before starting sprint, Studio user must confirm scope, agents, or milestone alignment |
| `CoverageBelowThreshold`   | QA coverage fails below required percent (e.g., 85%); human reviewer must approve continuation |
| `ManualGateOverride`       | Allows Studio user to approve `SprintClosed` even if one or more completion gates are unmet |
| `SprintPausedByStudio`     | Studio UI triggers a deliberate pause in sprint execution for strategy or dependency reasons |
| `AgentFailureRequiresReview` | A critical agent fails to emit valid outputs (e.g., missing test cases or trace linkage) |

---

### πŸ†˜ Escalation Triggers

| Condition                          | Result |
|------------------------------------|--------|
| Repeated failure of an agent (e.g., >3 retries) | Escalation to `HumanApprovalEscalator` |
| Incomplete trace matrix after sprint timeout | Sprint flagged for manual review |
| Security policy violation in output | Studio and Compliance Officer notified |
| Sprint scope mismatch with milestone | Block further progression without manual resolution |

---

### πŸ›‘ Studio Overrides (UI Buttons)

| Control               | Effect |
|-----------------------|--------|
| **πŸ›‘ Pause Sprint**     | Halts all downstream agent execution |
| **βœ… Approve Sprint Start** | Signals coordinator to activate FSM |
| **πŸ” Retry Agent**      | Resubmits prompt/task to failed agent |
| **πŸ”“ Close Sprint (Manual)** | Forces `SprintClosed` emission |
| **✏️ Edit Sprint Scope** | Updates `sprint-definition.json` before reactivation |

---

### πŸ” Controlled Bypass Flags

Injected into `sprint-definition.json` or Studio form:

```json
{
  "manual_override": true,
  "allow_unmet_gates": true,
  "approver": "studio-admin"
}
````

This allows authorized users to bypass automated failure stops with full trace logging.

---

### πŸ“Š Audit Logging

All manual interventions are recorded in:

* `intervention-events.json`
* Studio audit logs (with user ID, action, reason, timestamp)
* Sprint FSM history for compliance reporting

---

### βœ… Summary

Human intervention hooks provide:

* 🧭 **Governance without disruption**
* πŸ” **Control without removing automation**
* 🧾 **Full auditability of manual decisions**

The `SprintExecutionCoordinator` supports enterprise-grade **trust and transparency** while maintaining agentic speed and autonomy.

---

## Observability & Traceability

The `SprintExecutionCoordinator` is deeply integrated with the Factory’s observability-first architecture.  
It emits structured telemetry, traceable logs, and sprint-level execution metrics to ensure **real-time visibility**, **cross-agent correlation**, and **audit-ready histories**.

> β€œEvery sprint execution step, agent action, and artifact must be traceable to a sprint and milestone.”

---

### πŸ“‘ Trace Context Fields

All events, artifacts, logs, and metrics include the following:

| Field           | Description |
|------------------|-------------|
| `sprint_id`       | Unique sprint execution ID (e.g., `sprint-2025-06-MVP2`) |
| `milestone_id`    | Parent milestone ID (e.g., `mvp-ready`) |
| `trace_id`        | Global orchestration trace ID for observability |
| `feature_id`      | Feature executed by an agent |
| `agent_id`        | Agent type (e.g., `BackendDeveloperAgent`) |
| `skill_id`        | Skill invoked (e.g., `GenerateHandler`) |
| `status`          | `success`, `error`, `pending`, `blocked`, `manual_override` |
| `duration_ms`     | Total execution time (per agent or per feature) |

---

### πŸ“Š Metrics Emitted

| Metric Name                         | Type     | Description |
|-------------------------------------|----------|-------------|
| `sprint_execution_duration_ms`      | Timer    | Total time from `SprintStarted` to `SprintClosed` |
| `agent_execution_count`             | Counter  | Number of agents executed during sprint |
| `feature_completion_percent`        | Gauge    | % of planned features completed |
| `qa_coverage_percent`               | Gauge    | Final test coverage percent |
| `trace_matrix_validation_passed`    | Boolean  | Whether the sprint-trace-matrix is complete and valid |
| `manual_interventions_count`        | Counter  | How many times humans paused or intervened |

These are pushed to:
- Prometheus / Grafana dashboards
- Azure Monitor / Application Insights
- Studio execution dashboards

---

### 🧡 Observability Spans

Each agent execution step includes a span:

```json
{
  "span": "AgentExecution",
  "trace_id": "trace-abc123",
  "sprint_id": "sprint-2025-06-MVP2",
  "feature_id": "BookingFlow",
  "agent": "TestGeneratorAgent",
  "skill": "GenerateSpecFlow",
  "duration_ms": 1142,
  "status": "success"
}
````

Spans are emitted through:

* OpenTelemetry instrumentation
* Structured logs
* CI/CD trace pipelines

---

### πŸ“ Logged Artifacts

| Artifact File               | Description                               |
| --------------------------- | ----------------------------------------- |
| `sprint-trace-matrix.json`  | Links features β†’ agents β†’ artifacts/tests |
| `execution-metadata.json[]` | Per-agent execution logs                  |
| `qa-validation-report.md`   | Optional test coverage summary            |
| `intervention-events.json`  | Human overrides and escalation logs       |

---

### πŸ“Š Studio Sprint Visualization

The coordinator integrates with the Studio’s visual layer:

* Sprint Timeline: real-time execution view
* Agent Activity Table: who did what, when, with trace links
* QA Coverage Grid: feature Γ— test matrix per sprint
* Intervention Log: review and audit manual decisions

---

### βœ… Summary

Through structured telemetry, span injection, and trace-anchored outputs,
the `SprintExecutionCoordinator` makes **every sprint step observable and explainable** β€” enabling real-time tracking, post-mortem analysis, and compliance audits.

---

## Configuration

The behavior of the `SprintExecutionCoordinator` is configurable to adapt to different governance models, execution environments, and project maturity levels.

These configuration settings can be defined:

- Per project (e.g., in `orchestration-config.yaml`)
- Globally across the Factory
- Dynamically via `SprintPlanned` event payload

---

### βš™οΈ YAML Configuration Example

```yaml
SprintExecutionCoordinator:
  enableCheckpoint: true
  defaultCoverageThreshold: 90
  retryLimitPerAgent: 2
  allowManualOverrides: true
  requireSprintApproval: false
  autoCloseSprint: true
  observability:
    emitSpans: true
    logLevel: info
    metricsEnabled: true
  escalationPolicy:
    enabled: true
    notifyRoles: [ "product-owner", "qa-lead" ]
    fallbackCoordinator: "HumanApprovalEscalator"
````

---

### 🧩 Key Configuration Fields

| Field                      | Description                                             |
| -------------------------- | ------------------------------------------------------- |
| `enableCheckpoint`         | Enables mid-sprint checkpoint event/validation          |
| `defaultCoverageThreshold` | QA coverage gate (%); required to emit `SprintClosed`   |
| `retryLimitPerAgent`       | Maximum number of retries per agent per feature         |
| `allowManualOverrides`     | Allows Studio users to bypass failed gates (logged)     |
| `requireSprintApproval`    | Prevents sprint activation until manually approved      |
| `autoCloseSprint`          | Automatically emits `SprintClosed` if all gates pass    |
| `observability.emitSpans`  | Enables OpenTelemetry tracing for each agent skill call |
| `escalationPolicy.enabled` | Enables intervention flow if blockers are encountered   |

---

### 🧠 Runtime Config Injection

Config values may also be injected via:

* The `SprintPlanned` event payload
* A global environment preset
* Overrides stored in `sprint-definition.json` (for sprint-specific behavior)

This allows both **global policies** and **context-aware sprint tuning**.

---

### πŸ“ File Location and Inheritance

| Source                              | Scope                                 |
| ----------------------------------- | ------------------------------------- |
| `/config/orchestration-config.yaml` | Global defaults for all sprints       |
| `/planning/sprint-definition.json`  | Sprint-specific overrides             |
| Studio UI (editable fields)         | For manual configuration in real-time |

---

### βœ… Summary

Configuration allows the `SprintExecutionCoordinator` to adapt to:

* πŸŽ›οΈ Different governance levels (from autonomous to human-reviewed)
* πŸ“ˆ Varying QA maturity (strict vs. flexible coverage gates)
* πŸ” Retry and resilience policies
* πŸ” Security and observability controls

This flexibility ensures the Factory can operate at scale while staying **policy-aligned and team-appropriate**.

---

## Error Handling & Resilience

The `SprintExecutionCoordinator` is built with robust error handling and resilience mechanisms to ensure sprint execution can continue β€” or recover β€” even in the presence of partial failures, agent misbehavior, or environmental issues.

Its design embraces **idempotency**, **structured retries**, and **graceful escalation**.

---

### πŸ›  Error Categories and Recovery Strategies

| Error Type                   | Handling Strategy |
|------------------------------|-------------------|
| **Agent Execution Failure**   | Retry up to `retryLimitPerAgent`, then escalate |
| **Missing Artifact**          | Transition to `Blocked`, notify QA and Studio |
| **Test Coverage Below Threshold** | Pause or require manual approval to continue |
| **Trace Mismatch or Invalid Output** | Reject sprint close, emit validation error |
| **Observability Failure**     | Retry span injection; escalate if telemetry fails |
| **CI/CD Pipeline Tagging Error** | Defer handoff to `PipelineGenerator`, retry if possible |

---

### πŸ” Retry Behavior

| Trigger                    | Configurable? | Retry Default |
|----------------------------|----------------|----------------|
| Agent failure (`status: error`) | βœ… via `retryLimitPerAgent` | 2 attempts |
| Span injection or trace write | βœ… | 3 attempts |
| Invalid artifact (e.g., file missing fields) | βœ… | 1 attempt, else manual review |

Retry actions are logged in `execution-metadata.json` and Studio dashboards for traceability.

---

### ⏸ Sprint FSM State Transitions on Error

```mermaid
stateDiagram-v2
    Active --> Blocked: MissingArtifact or FailedValidation
    Blocked --> Active: ManualFix or RetryTrigger
    Active --> Checkpoint: MidSprintPause
    Blocked --> Escalated: HumanInterventionRequired
    Escalated --> Active: ResumedAfterApproval
````

---

### 🧠 Internal State Flags

| Flag                  | Meaning                                          |
| --------------------- | ------------------------------------------------ |
| `isBlocked`           | True if sprint FSM moved to Blocked state        |
| `hasEscalated`        | True if manual review was triggered              |
| `agentRetryHistory[]` | Stores retry attempts per agent/feature/skill    |
| `overrideRequested`   | True if Studio user manually forced continuation |

---

### 🧾 Error Artifacts

| File                        | Contents                                                     |
| --------------------------- | ------------------------------------------------------------ |
| `execution-errors.json`     | List of failed agents, retry attempts, and resolution status |
| `intervention-events.json`  | Records of human approvals, manual transitions               |
| `blocked-sprint-summary.md` | Summary of blockers, missing outputs, test gaps              |

---

### πŸ“£ Studio and Alerting

* 🟠 Warnings shown in Sprint Dashboard
* πŸ”΄ Blockers emit real-time notification to approver roles
* πŸ” Retry buttons available per agent in UI
* ✏️ Manual fix injection (e.g., fix trace metadata or retry coverage analysis)

---

### βœ… Summary

The `SprintExecutionCoordinator` is designed to:

* Retry safely when possible
* Block progression when required
* Escalate only with full trace context
* Log and visualize every failure for diagnosis and governance

This ensures **resilient, traceable, sprint execution** β€” even in imperfect conditions.

---

## Integration with MilestoneLifecycleCoordinator

The `SprintExecutionCoordinator` operates in close alignment with the `MilestoneLifecycleCoordinator`, ensuring that **sprints contribute toward milestone progression**, and that no milestone can be completed unless all of its sprints have been validated and trace-complete.

This coordination ensures both **execution granularity (sprint)** and **delivery alignment (milestone)**.

---

### πŸ” Communication Between Coordinators

| Direction        | Trigger / Event                | Payload |
|------------------|--------------------------------|---------|
| Milestone β†’ Sprint | `SprintPlanned`, `MilestoneReady` | Sprint scope, trace ID, milestone goal |
| Sprint β†’ Milestone | `SprintClosed`                 | Feature completion, coverage %, trace matrix |
| Sprint β†’ Milestone | `SprintBlocked`, `SprintEscalated` | Error reason, retry history, manual approval request |

---

### πŸ“˜ Sprint Contribution to Milestone Gates

Each milestone in `milestones.yaml` lists required features:

```yaml
milestones:
  - id: mvp-ready
    requiredFeatures:
      - BookingFlow
      - Notification.Send
      - Auth.Login
    gateConditions:
      - allSprintsClosed
      - sprintTraceMatrixComplete
      - testCoverageAbove: 90
````

The `MilestoneLifecycleCoordinator` checks:

* Has every required `feature_id` been completed in one or more sprints?
* Are all associated sprints closed and QA-verified?
* Does the aggregated `sprint-trace-matrix.json` cover milestone scope?

---

### 🧠 Trace Propagation Model

| Level        | Trace Field                                              |
| ------------ | -------------------------------------------------------- |
| Sprint       | `sprint_id`, `trace_id`, `milestone_id`                  |
| Agent Output | Includes all above fields + `feature_id`, `skill_id`     |
| Milestone    | Aggregates sprint closures and matrix validation reports |

This enables full backward tracing:
**Milestone β†’ Sprint(s) β†’ Feature β†’ Artifact β†’ Agent**

---

### πŸ“€ Event Example: `SprintClosed`

```json
{
  "event": "SprintClosed",
  "sprint_id": "sprint-2025-07-MVP2",
  "milestone_id": "mvp-ready",
  "trace_id": "trace-xyz-456",
  "features": ["BookingFlow", "Notification.Send"],
  "qa_coverage": 91.3,
  "status": "complete"
}

Consumed by:

  • MilestoneLifecycleCoordinator
  • Studio dashboards
  • CI/CD pipeline stage gates

πŸ” Coordinated Compliance

  • Test coverage gates enforced at sprint level
  • Artifact tagging linked to both sprint and milestone IDs
  • CI/CD stages for release promotion gated by MilestoneReached only after all dependent SprintClosed events pass

βœ… Summary

The SprintExecutionCoordinator and MilestoneLifecycleCoordinator work together to:

  • Maintain modular execution via sprints
  • Guarantee delivery integrity via milestone gates
  • Provide end-to-end traceability from feature to release

This layered coordination ensures scale without chaos and speed with structure.


CI/CD Trace Injection: Tagging and Artifact Metadata

The SprintExecutionCoordinator plays a key role in preparing all generated artifacts β€” including code, tests, containers, and release manifests β€” for CI/CD alignment and traceability.

By injecting trace metadata at the sprint level, it ensures that every artifact is linked to a sprint, milestone, and feature, enabling:

  • 🧾 Auditable releases
  • πŸ” Reproducible builds
  • πŸ“¦ Tagged Docker images and Git commits
  • πŸ“Š Build pipeline trace dashboards

🧬 Metadata Fields Injected

Field Where Injected
sprint_id Git commit messages, image tags, execution logs
trace_id execution-metadata.json, logs, observability spans
milestone_id Deployment manifests, trace matrix
feature_id Artifact file headers, test annotations
agent_id Skill logs and telemetry entries

πŸ“ Artifacts with Trace Tags

Artifact Type Injection Point
Git Commit commit-msg: "[sprint:sprint-06] [trace:xyz] Add BookingHandler"
Docker Image booking-service:1.0.3-sprint06-mvp-v1
Pipeline Logs Includes trace_id, sprint_id, and agent_id
Release Notes / Markdown Includes footer block with trace context
Test Cases SpecFlow tag: @SprintId(sprint-2025-07)

πŸ“¦ CI/CD Pipeline Integration

Once the SprintClosed event is emitted and validated:

  • PipelineGenerator picks up sprint-trace-matrix.json
  • Builds and releases are tagged using values from:
  • sprint_id
  • milestone_id
  • trace_id

βœ… Example:

variables:
  sprint_id: sprint-2025-07
  milestone_id: mvp-ready
  trace_id: trace-7482bfa3

steps:
  - task: Docker@2
    inputs:
      tags: |
        $(sprint_id)
        $(milestone_id)
        trace:$(trace_id)
````

---

### πŸ” Deployment Trace Anchoring

Deployed artifacts (e.g., Helm charts, ARM templates) include metadata annotations:

```yaml
metadata:
  labels:
    sprint: sprint-2025-07
    milestone: mvp-ready
    trace: trace-7482bfa3

β†’ Enables reverse tracing from production environment back to the planning intent.


πŸ“Š Studio Build Trace View

Artifact Sprint Milestone Image Tag CI/CD Status
Booking API sprint-2025-07 mvp-ready booking:1.0.3-sprint07 βœ… Passed
Auth Service sprint-2025-06 auth-preview auth:0.9.1-sprint06 ⚠️ Retrying

βœ… Summary

The SprintExecutionCoordinator guarantees that every artifact generated during a sprint is trace-linked, tagged, and CI/CD-compatible.

This enables:

  • πŸ”— End-to-end traceability from blueprint to deployment
  • 🚦 Milestone-driven promotion gates
  • πŸ“¦ Artifact governance across environments

Studio Visualizations: Sprint Cards, Dashboards, and Trace Matrix

The ConnectSoft Studio provides a rich set of visualizations to monitor, validate, and govern sprint execution.
These views are powered directly by outputs from the SprintExecutionCoordinator β€” including events, trace files, QA reports, and observability metrics.

Sprint execution becomes observable, navigable, and actionable via Studio’s sprint dashboards.


🧩 Sprint Overview Card

Each active or completed sprint is shown as a card in the Studio UI:

Field Source
Sprint ID sprint-definition.json
Milestone Link milestone_id from sprint
Feature Count Number of scoped feature_id[]
QA Status From qa-validation-report.md
Coverage % Calculated from trace matrix
Duration Time between SprintStarted and SprintClosed
Agent Health Aggregated from execution-metadata.json
Progress Derived from trace and artifact readiness

πŸ“Š Sprint Trace Matrix View

Interactive table populated from sprint-trace-matrix.json:

Feature Agents Executed Artifacts Tests Status
BookingFlow BackendDev, QAAgent 3 files 2 test cases βœ… Done
SendEmail TestGenAgent 2 files 1 test case ⚠️ Incomplete
RetryMechanism BackendDev 0 0 ❌ Blocked

🟒 Rows link to logs, trace IDs, and file diffs


πŸ“ˆ Sprint Timeline

```mermaid gantt title Sprint Timeline β€” sprint-2025-07-MVP2 dateFormat YYYY-MM-DD section Sprint Phases Planning :done, s0, 2025-05-12,1d Active Execution :active, s1, 2025-05-13,2d QA Validation : s2, 2025-05-15,1d Sprint Closure : s3, 2025-05-16,0.5d ````

β†’ Annotated with failure/retry markers, manual interventions, and trace logs


πŸ“ Agent Activity Breakdown

Bar chart per agent:

  • Total skills invoked
  • Avg duration
  • Success/failure ratio
  • Linked trace ID count

Filtered by:

  • Sprint
  • Feature
  • Milestone

🧯 Intervention Panel

Shows manual approvals, blocked states, retry attempts:

Event Type Agent Timestamp Outcome
Retry Request QAAgent 2025-05-14T10:32Z βœ… Passed
Manual Close Override Studio Admin 2025-05-15T17:04Z 🟑 Partial Trace
Agent Failure TestGenAgent 2025-05-14T08:23Z ❌ No Output

πŸ“Ž Trace Explorer Integration

From any sprint card or row, user can launch:

  • Trace-to-Code Path: trace β†’ agent β†’ skill β†’ file β†’ commit
  • Trace-to-Test: trace β†’ feature β†’ test β†’ coverage
  • Trace-to-Artifact: trace β†’ build β†’ image β†’ CI/CD result

βœ… Summary

Studio visualizations powered by the SprintExecutionCoordinator provide:

  • 🧠 Real-time sprint monitoring
  • βœ… Visual validation of gates, coverage, and agent activity
  • πŸ” Trace-aware diagnostics for debugging or compliance

Real-World Example Sprint: Notification Service MVP Sprint

This example illustrates how the SprintExecutionCoordinator orchestrated a real sprint for the Notification Service, demonstrating full traceable execution β€” from sprint planning to milestone completion.


πŸ“˜ Sprint Overview

Property Value
sprint_id sprint-2025-05-notify-mvp
milestone_id mvp-ready
trace_id trace-d56a12fa
features SendEmail, RetryNotification, SendPush
agents BackendDeveloperAgent, TestGeneratorAgent, QAAgent
coverageThreshold 90%
checkpointEnabled βœ… Yes

🧩 Inputs

sprint-definition.json:

```json { "sprint_id": "sprint-2025-05-notify-mvp", "milestone_id": "mvp-ready", "features": ["SendEmail", "RetryNotification", "SendPush"], "agents": ["BackendDeveloperAgent", "TestGeneratorAgent", "QAAgent"], "trace_id": "trace-d56a12fa", "checkpoints": 1, "testCoverageThreshold": 90 } ````


πŸ” Execution Flow

  1. SprintPlanned event triggered by ProductOwnerAgent
  2. SprintExecutionCoordinator loaded plan, transitioned to Active
  3. Agents activated:
    • BackendDeveloperAgent created handlers
    • TestGeneratorAgent emitted SpecFlow and unit tests
    • QAAgent validated artifacts and generated coverage report
  4. All agents' outputs linked via trace_id and written to:
    • execution-metadata.json
    • sprint-trace-matrix.json
  5. Mid-sprint checkpoint passed without intervention
  6. SprintClosed emitted after 92.1% test coverage achieved

πŸ“¦ Outputs

  • execution/BookingHandler.cs
  • tests/NotificationFlow.feature
  • sprint-trace-matrix.json
  • qa-validation-report.md
  • SprintClosed event emitted
  • Tagged image: notification-service:1.0.0-sprint05

πŸ“Š Studio View Snapshot

Feature Artifacts Tests QA Status Result
SendEmail EmailHandler.cs βœ… 3 test cases βœ… Pass βœ… Done
RetryNotification RetryHandler.cs βœ… 2 test cases βœ… Pass βœ… Done
SendPush PushHandler.cs βœ… 2 test cases βœ… Pass βœ… Done

πŸ“ˆ Metrics Summary

  • Total agent executions: 9
  • Average agent duration: 1.28 sec
  • QA coverage: 92.1%
  • Manual interventions: 0
  • Status: βœ… Sprint success
  • Time-to-completion: 4m 17s

🎯 Outcome

  • MilestoneLifecycleCoordinator received SprintClosed
  • PipelineGenerator triggered build and release tagging
  • Sprint artifacts were promoted to staging via mvp-ready milestone gate

βœ… Summary

This real-world sprint demonstrated:

  • πŸ”„ Coordinated agent execution per feature
  • πŸ§ͺ Enforced QA validation gates
  • πŸ”— End-to-end traceability via sprint_id and trace_id
  • πŸ“¦ Deployment-ready CI/CD handoff

The SprintExecutionCoordinator enabled structured, observable, and governable delivery from intent to artifact β€” all in minutes.