workflow-orchestrator

charon-fan/agent-playbook · updated Apr 8, 2026

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$npx skills add https://github.com/charon-fan/agent-playbook --skill workflow-orchestrator
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summary

A skill that automatically coordinates workflows across multiple skills, triggering follow-up actions at appropriate milestones.

skill.md

Workflow Orchestrator

A skill that automatically coordinates workflows across multiple skills, triggering follow-up actions at appropriate milestones.

When This Skill Activates

This skill should be triggered automatically when:

  • A skill completes its main workflow
  • A milestone is reached (PRD complete, implementation done, etc.)
  • User says "complete workflow" or "finish the process"

How It Works

┌─────────────────────────────────────────────────────────────┐
│                    Workflow Orchestration                   │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  1. Detect Milestone → 2. Read Hooks → 3. Execute Chain    │
│                                                             │
│  prd-planner complete                                       │
│       ↓                                                     │
│  workflow-orchestrator                                      │
│       ↓                                                     │
│  ┌─────────────────────────────────────┐                   │
│  │ auto-trigger self-improving-agent   │ (background)       │
│  │ auto-trigger session-logger         │ (auto)            │
│  └─────────────────────────────────────┘                   │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Trigger Configuration

Read trigger definitions from skills/auto-trigger/SKILL.md:

hooks:
  after_complete:
    - trigger: self-improving-agent
      mode: background
    - trigger: session-logger
      mode: auto
  on_error:
    - trigger: self-improving-agent
      mode: background

Execution Modes

Mode Behavior Use When
auto Execute immediately, no confirmation Logging, status updates
background Execute without blocking Reflection, analysis
ask_first Ask user before executing PRs, deployments, major changes

Milestone Detection

PRD Complete

Detected when:
- docs/{scope}-prd.md exists
- All phases in {scope}-prd-task-plan.md are checked
- Status shows "COMPLETE"

Actions:
1. Trigger self-improving-agent (background)
2. Trigger session-logger (auto)

Implementation Complete

Detected when:
- All PRD requirements implemented
- Tests pass
- Code committed

Actions:
1. Trigger code-reviewer (ask_first)
2. Trigger create-pr if changes staged
3. Trigger session-logger (auto)

Self-Improvement Complete

Detected when:
- Reflection complete
- Patterns abstracted
- Skill files modified

Actions:
1. Trigger create-pr (ask_first)
2. Trigger session-logger (auto)

Universal Learning (Any Skill Complete)

Detected when:
- ANY skill completes its workflow
- User provides feedback
- Error or issue encountered

Actions:
1. Trigger self-improving-agent (background)
2. Trigger session-logger (auto)

The self-improving-agent:
- Extracts experience from completed skill
- Identifies patterns and insights
- Updates related skills with learned patterns
- Consolidates memory for future reference

Error Handling (on_error)

Detected when:

  • A command returns non-zero exit code
  • Tests fail after following skill guidance
  • User reports the guidance produced incorrect results

Actions:

  1. Trigger self-improving-agent (background) for self-correction
  2. Trigger session-logger (auto) to capture error context

Hook Implementation in Skills

To enable auto-trigger, add this section to any skill's SKILL.md:

## Auto-Trigger (After Completion)

When this skill completes, automatically trigger:

```yaml
hooks:
  after_complete:
    - trigger: skill-name
      mode: auto|background|ask_first
      context: "relevant context"
  on_error:
    - trigger: self-improving-agent
      mode: background

Current Skill Hooks

  • prd-planner: After PRD complete → self-improving-agent + session-logger
  • self-improving-agent: After improvement → create-pr + session-logger
  • prd-implementation-precheck: After implementation → self-improving-agent + session-logger
  • code-reviewer: After review → self-improving-agent + session-logger
  • debugger: After debugging → self-improving-agent + session-logger
  • create-pr: After PR created → session-logger
  • session-logger: No trigger (terminates chain)

Universal Learning Pattern

┌─────────────────────────────────────────────────────────────┐
│                  ANY Skill Completes                        │
└──────────────┬──────────────────────────────────────────────┘
    ┌──────────────────────┐
    │ workflow-orchestrator │
    └──────────┬───────────┘
    ┌──────────┴─────────┐
    ↓                   ↓
self-improving-agent  session-logger
    ↓                   ↓
Learn from experience  Save context
    ↓                   ↓
Update skills         Log session
create-pr (if modified)

## Workflow Examples

### Example 1: PRD Creation Workflow

User: "Create a PRD for user authentication" ↓ prd-planner executes ↓ Phase 6 complete: PRD delivered ↓ workflow-orchestrator detects milestone ↓ ┌─────────────────────────────────┐ │ Background: self-improving-agent │ → Learns from PRD patterns │ Auto: session-logger │ → Saves session └─────────────────────────────────┘


### Example 2: Full Feature Workflow

User: "Create a PRD and implement it" ↓ prd-planner → workflow-orchestrator ↓ self-improving-agent → workflow-orchestrator ↓ prd-implementation-precheck ↓ implementation complete → workflow-orchestrator ↓ code-reviewer → self-improving-agent → workflow-orchestrator ↓ create-pr → workflow-orchestrator ↓ session-logger


Each step triggers `self-improving-agent` to learn from the experience.

## Implementation Steps

### Step 1: Detect Milestone

Check for completion indicators:

```bash
# PRD complete?
grep -q "COMPLETE" docs/{scope}-prd-task-plan.md

# All phases checked?
grep -q "^\- \[x\].*Phase 6" docs/{scope}-prd-task-plan.md

# PRD file exists?
ls docs/{scope}-prd.md

Step 2: Read Trigger Config

# Read hooks from auto-trigger skill
cat skills/auto-trigger/SKILL.md

Step 3: Execute Hooks

For each hook in order (before_start, after_complete, on_error):

  1. Check if condition is met
  2. Execute based on mode
  3. Pass context to triggered skill
  4. Wait/continue based on mode

Step 4: Update Status

Log what was triggered and the result:

## Workflow Execution

- [x] self-improving-agent (background) - Started
- [x] session-logger (auto) - Session saved
- [ ] create-pr (ask_first) - Pending user approval

Skills with Auto-Trigger

Skill Triggers After
prd-planner self-improving-agent, session-logger
self-improving-agent create-pr, session-logger
prd-implementation-precheck code-reviewer, session-logger
code-reviewer self-improving-agent, session-logger
create-pr session-logger
refactoring-specialist self-improving-agent, session-logger
debugger self-improving-agent, session-logger

Adding Auto-Trigger to Existing Skills

To add auto-trigger capability to an existing skill, add to the end of its SKILL.md:

---

## Auto-Trigger

When this skill completes, automatically trigger:

```yaml
hooks:
  after_complete:
    - trigger: session-logger
      mode: auto
      context: "Save session context"

For more complex triggers, specify mode and context:

```markdown
## Auto-Trigger

When this skill completes:

```yaml
hooks:
  after_complete:
    - trigger: next-skill
      mode: background
      context: "Description"
    - trigger: session-logger
      mode: auto
      context: "Save session"
    - trigger: create-pr
      mode: ask_first
      context: "Create PR if files modified"
  on_error:
    - trigger: self-improving-agent
      mode: background

## Best Practices

1. **Always log to session** - Every workflow should end with session-logger
2. **Ask before major actions** - PRs, deployments, destructive changes
3. **Background for analysis** - Reflection, evaluation, optimization
4. **Auto for status** - Logging, status updates, bookmarks
5. **Don't create loops** - Ensure chains terminate
how to use workflow-orchestrator

How to use workflow-orchestrator on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add workflow-orchestrator
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/charon-fan/agent-playbook --skill workflow-orchestrator

The skills CLI fetches workflow-orchestrator from GitHub repository charon-fan/agent-playbook and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/workflow-orchestrator

Reload or restart Cursor to activate workflow-orchestrator. Access the skill through slash commands (e.g., /workflow-orchestrator) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.643 reviews
  • Anaya Rao· Dec 24, 2024

    Solid pick for teams standardizing on skills: workflow-orchestrator is focused, and the summary matches what you get after install.

  • Daniel Martin· Dec 16, 2024

    workflow-orchestrator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Dhruvi Jain· Dec 12, 2024

    workflow-orchestrator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Diego Haddad· Dec 12, 2024

    Keeps context tight: workflow-orchestrator is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Advait Johnson· Dec 12, 2024

    We added workflow-orchestrator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Rahul Santra· Nov 11, 2024

    We added workflow-orchestrator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Omar Wang· Nov 7, 2024

    Solid pick for teams standardizing on skills: workflow-orchestrator is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 3, 2024

    I recommend workflow-orchestrator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diego Thomas· Nov 3, 2024

    workflow-orchestrator has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Brown· Oct 26, 2024

    workflow-orchestrator has been reliable in day-to-day use. Documentation quality is above average for community skills.

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