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Agentic Workflows

hve-core uses GitHub Agentic Workflows to automate the journey from issue creation through implementation, code review, and dependency management. Five event-driven workflows connect specialized agents into a pipeline where each stage triggers the next through labels, pull requests, and GitHub events.

NOTE

GitHub Agentic Workflows is an experimental/beta feature. The workflows described here represent hve-core's early experiments with the technology and may evolve as the platform matures.

End-to-End Process Flow

flowchart TD
subgraph TRIGGER["Issue Created or Labeled"]
A["New issue opened<br/>or labeled needs-triage"]
end

subgraph TRIAGE["Issue Triage Workflow"]
B["Read issue title, body,<br/>and template metadata"]
C["Classify by type<br/>and component"]
D["Detect duplicates<br/>via keyword search"]
E["Assess issue quality"]
F{"Scope too broad<br/>for single deliverable?"}
G["Decompose into<br/>sub-issues"]
H{"Passes all<br/>agent-ready criteria?"}
I["Apply labels,<br/>remove needs-triage"]
J["Add agent-ready label"]
K["Leave for human<br/>review"]
end

subgraph IMPLEMENT["Issue Implementation Workflow"]
L["Read issue and<br/>acceptance criteria"]
M["Research codebase:<br/>files, patterns, conventions"]
N["Plan minimal<br/>change set"]
O["Implement changes"]
P["Verify against<br/>acceptance criteria"]
Q["Open pull request<br/>referencing the issue"]
end

subgraph REVIEW["PR Review Workflow"]
R["Detect PR opened<br/>or ready for review"]
S["Analyze diff against<br/>coding standards"]
T["Check conventions,<br/>security, quality"]
U{"Review passed?"}
V["Add review-passed label"]
W["Add needs-revision label<br/>with inline comments"]
end

subgraph HUMAN["Human Review"]
X["Maintainer reviews<br/>and merges"]
end

A --> B
B --> C
C --> D
D --> E
E --> F
F -- Yes --> G
G --> I
F -- No --> H
H -- Yes --> I
I --> J
H -- No --> I
I --> K
J --> L
L --> M
M --> N
N --> O
O --> P
P --> Q
Q --> R
R --> S
S --> T
T --> U
U -- Yes --> V
V --> X
U -- No --> W
W -.-> O

Workflow Details

WorkflowTriggerAgentKey Actions
Issue TriageIssue opened or labeled needs-triageIssue Triage AgentClassify, detect duplicates, assess quality, decompose, label, evaluate readiness
Issue ImplementationIssue labeled agent-readyTask Implementor AgentResearch codebase, plan changes, implement, open PR
PR ReviewPR opened or marked ready for reviewPR Review AgentReview correctness, conventions, security; label review-passed or needs-revision
Dependabot PR ReviewDependabot PR opened or updatedDependency Reviewer AgentValidate licensing, SHA pinning, environment sync; approve safe bumps
Documentation UpdatePush to mainDocumentation Update Checker AgentMap code changes to docs, create issues for stale documentation

TIP

The triage agent only classifies, labels, and optionally decomposes issues. It does not close issues, assign users, or modify issue titles.

NOTE

The implementation agent keeps PRs small and focused. If the issue is ambiguous or too large, it posts a comment requesting clarification instead of guessing.

Workflow Configuration

All five workflows are defined as GitHub Agentic Workflow markdown files under .github/workflows/ and compiled to lock files using gh aw compile:

Workflow FileLock FileTriggerAgent
issue-triage.mdissue-triage.lock.ymlIssue opened or labeled needs-triageIssue Triage Agent
issue-implement.mdissue-implement.lock.ymlIssue labeled agent-readyTask Implementor Agent
pr-review.mdpr-review.lock.ymlPR opened or marked ready for reviewPR Review Agent
dependency-pr-review.mddependency-pr-review.lock.ymlDependabot PR opened or updatedDependency Reviewer
doc-update-check.mddoc-update-check.lock.ymlPush to mainDocumentation Checker

Each workflow file declares permissions, safe output limits, and activation guards that prevent unintended execution.

Label-Driven Handoffs

Labels serve as the event bus connecting workflows. Each label transition triggers the next stage:

stateDiagram-v2
[*] --> needs_triage: Issue opened
needs_triage --> classified: Triage removes needs-triage,<br/>adds type + component labels
classified --> agent_ready: Triage adds agent-ready<br/>(if criteria met)
classified --> human_review: Criteria not met,<br/>awaits human labeling
agent_ready --> pr_opened: Implementation agent<br/>opens PR
pr_opened --> review_passed: Review agent approves
pr_opened --> needs_revision: Review agent requests changes
needs_revision --> pr_opened: Author pushes fixes
review_passed --> merged: Maintainer merges
merged --> [*]

Interactive Agent Workflows

Beyond the automated GitHub event-driven pipeline, hve-core provides interactive agents invoked through VS Code Copilot Chat. These agents support the manual side of the development lifecycle.

RPI Orchestration

The RPI Agent runs a five-phase iterative cycle: Research, Plan, Implement, Review, and Discover. It delegates to four specialized subagents:

AgentRole
Task ResearcherDeep codebase and domain analysis, produces research documents
Task PlannerCreates phased implementation plans with validation steps
Task ImplementorExecutes plans through subagent delegation and tracks changes
Task ReviewerValidates completed work against plans and conventions

Each agent hands off to the next through structured artifacts stored in .copilot-tracking/.

Prompt Engineering

The Prompt Builder orchestrates a three-phase workflow for creating and refining AI artifacts (agents, prompts, instructions, skills):

  1. Execute and evaluate prompt files using sandbox testing
  2. Research findings and best practices
  3. Apply modifications based on evaluation results

It delegates to Prompt Tester, Prompt Evaluator, Prompt Updater, and Researcher subagents.

Security Review

The Security Reviewer orchestrates OWASP-based vulnerability assessment through four subagents: Codebase Profiler, Skill Assessor, Finding Deep Verifier, and Report Generator. It supports audit, diff, and plan modes.

Code Review

The Functional Code Review agent analyzes branch diffs for logic errors, edge case gaps, and error handling deficiencies before code reaches a pull request. The PR Review agent provides comprehensive review after PR creation.

Documentation Operations

The Doc Ops agent audits documentation for style compliance, accuracy against implementation, and coverage gaps.

Backlog Management

The GitHub Backlog Manager coordinates five workflows (discovery, triage, sprint planning, execution, and quick add) for managing issue lifecycles. The ADO Backlog Manager provides equivalent capabilities for Azure DevOps work items.

Project Planning

Five agents support upstream planning activities:

AgentPurpose
BRD BuilderBusiness Requirements Documents
PRD BuilderProduct Requirements Documents
ADR CreationArchitecture Decision Records
Architecture Diagram BuilderVisual system architecture diagrams
Security Plan CreatorSecurity assessment and mitigation plans

How It All Connects

flowchart LR
subgraph AUTOMATED["Automated Pipeline"]
direction TB
TRIAGE["Issue Triage<br/><i>event-driven</i>"]
IMPL["Issue Implementation<br/><i>event-driven</i>"]
REVIEW["PR Review<br/><i>event-driven</i>"]
DEPEND["Dependabot PR Review<br/><i>event-driven</i>"]
DOCS["Doc Update Check<br/><i>event-driven</i>"]
TRIAGE -- "agent-ready label" --> IMPL
IMPL -- "opens PR" --> REVIEW
end

subgraph INTERACTIVE["Interactive Agents"]
direction TB
RPI["RPI Orchestration"]
PB["Prompt Builder"]
SR["Security Reviewer"]
CR["Code Review"]
DOC["Doc Ops"]
BM["Backlog Manager"]
PP["Project Planning"]
end

subgraph ARTIFACTS["Shared Artifacts"]
direction TB
INST["Instructions<br/>.github/instructions/"]
TRACK[".copilot-tracking/<br/>plans, research, changes"]
LABELS["GitHub Labels<br/>and Milestones"]
end

AUTOMATED --> INST
INTERACTIVE --> INST
RPI --> TRACK
BM --> LABELS
TRIAGE --> LABELS

The automated pipeline and interactive agents share instruction files for consistent coding standards. Interactive agents produce tracking artifacts that inform implementation. The automated pipeline uses GitHub labels as its coordination mechanism, while interactive agents coordinate through .copilot-tracking/ files.


🤖 Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.