zhaono1/agent-playbook

workflow-orchestrator

Coordinates multi-skill workflows and records or runs follow-up actions when the host runtime supports them. Use when completing PRD creation, implementation, or any milestone that should be evaluated for additional skills.

First seen Jan 22, 2026

Installation

$ npx skills add zhaono1/agent-playbook --skill workflow-orchestrator

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 77
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Allowed toolsRead, Write, Edit, Bash, Grep, AskUserQuestion
More metadata
hooks
{"after_complete":{"0":"trigger: session-logger","mode":"auto","reason":"Save workflow execution context"}}

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 10,764 B
  • docs README.md 722 B
  • docs SUMMARY.md 249 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 819 installs

SKILL.md

Workflow Orchestrator

A skill that coordinates workflows across multiple skills by evaluating hook metadata, recording pending follow-ups, and running only the actions that are safe and supported in the current host runtime.

When This Skill Activates

This skill should be used 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. Record/Run Safe Follow-ups │
│                                                             │
│  prd-planner complete                                       │
│       ↓                                                     │
│  workflow-orchestrator                                      │
│       ↓                                                     │
│  ┌─────────────────────────────────────┐                   │
│  │ declared self-improving follow-up   │ (record/run)       │
│  │ declared session logging follow-up  │ (record/run)       │
│  └─────────────────────────────────────┘                   │
│                                                             │
└─────────────────────────────────────────────────────────────┘

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 Run or record a low-risk follow-up when the host supports it Logging, status updates
background Record a non-blocking follow-up 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. Record self-improving-agent as a background follow-up
2. Run or record session-logger if the host supports it

Implementation Complete

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

Actions:
1. Ask before running code-reviewer
2. Run create-pr only when the user requested submission
3. Run or record session-logger if the host supports it

Self-Improvement Applied

Detected when:
- Candidate validated with auditable evidence
- One named durable owner changed
- Representative behavior rerun
- Candidate recorded as applied

Actions:
1. Ask before running create-pr
2. Run or record session-logger if the host supports it

Learning Candidate (Skill Complete)

Detected when:
- A skill completes its workflow and produces reusable evidence
- User provides feedback
- Error or issue encountered

Actions:
1. Record self-improving-agent as a background follow-up
2. Run or record session-logger if the host supports it

The self-improving-agent:
- Captures a candidate only when reusable evidence exists
- Excludes raw transcripts and private tool payloads
- Keeps uncertain findings under observation
- Validates candidates only with explicit, auditable evidence
- Applies validated changes only to a named durable owner with a change reference
- Proves the representative behavior after application

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. Record self-improving-agent (background) for self-correction
  2. Run or record session-logger to capture error context

Hook Implementation in Skills

To declare follow-up metadata, add this section to any skill's SKILL.md:

## Auto-Trigger (After Completion)

When this skill completes, record or run supported follow-ups:

hooks: aftercomplete: - trigger: skill-name mode: auto|background|askfirst context: "relevant context" on_error: - trigger: self-improving-agent mode: background


### Current Hook Contract

Hook metadata is declarative intent, not proof of CLI automation. Read the
current skill front matter before acting. An absent hook means no declared
follow-up; an existing hook still requires host support and the permission
boundary for the target action.

### Universal Learning Pattern

┌─────────────────────────────────────────────────────────────┐ │ Skill Completes With Evidence │ └──────────────┬──────────────────────────────────────────────┘ │ ↓ ┌──────────────────────┐ │ workflow-orchestrator │ └──────────┬───────────┘ │ ┌──────────┴─────────┐ ↓ ↓ self-improving-agent session-logger ↓ ↓ Capture candidate Save bounded context ↓ ↓ Validate evidence Log session ↓ Apply to named owner ↓ create-pr (only if submission was requested)

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 │ → Records learning proposal
│ Auto: session-logger             │ → Saves session when supported
└─────────────────────────────────┘

Example 2: Full Feature Workflow

User: "Create a PRD and implement it"
        ↓
prd-planner → workflow-orchestrator
        ↓
self-improving-agent (candidate capture only)
        ↓
prd-implementation-precheck
        ↓
implementation complete → workflow-orchestrator
        ↓
code-reviewer → optional candidate capture
        ↓
create-pr (only when requested) → workflow-orchestrator
        ↓
session-logger

Each milestone can produce a self-improving-agent follow-up, but durable skill edits still require validation or explicit approval.

Implementation Steps

Step 1: Detect Milestone

Check for completion indicators:

# 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: Record or Execute Hooks

For each hook in order (beforestart, aftercomplete, on_error):

  1. Check if condition is met
  2. Record or execute based on mode and host support
  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 No automatic PR; applied changes may declare a logging follow-up
prd-implementation-precheck self-improving-agent, 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 Follow-up Metadata to Existing Skills

To add follow-up metadata to an existing skill, add to the end of its SKILL.md:

---

## Auto-Trigger

When this skill completes, record or run supported follow-ups:

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

For more complex triggers, specify mode and context:

## Auto-Trigger

When this skill completes:

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

Best Practices

  1. Log only when supported and appropriate - Session logging is a bounded optional follow-up
  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