orchestrate

hyperb1iss/hyperskills · updated Apr 8, 2026

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$npx skills add https://github.com/hyperb1iss/hyperskills --skill orchestrate
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summary

Meta-orchestration patterns mined from 597+ real agent dispatches across production codebases. This skill tells you WHICH strategy to use, HOW to structure prompts, and WHEN to use background vs foreground.

skill.md

Multi-Agent Orchestration

Meta-orchestration patterns mined from 597+ real agent dispatches across production codebases. This skill tells you WHICH strategy to use, HOW to structure prompts, and WHEN to use background vs foreground.

Core principle: Choose the right orchestration strategy for the work, partition agents by independence, inject context to enable parallelism, and adapt review overhead to trust level.

Strategy Selection

digraph strategy_selection {
    rankdir=TB;
    "What type of work?" [shape=diamond];

    "Research / knowledge gathering" [shape=box];
    "Independent feature builds" [shape=box];
    "Sequential dependent tasks" [shape=box];
    "Same transformation across partitions" [shape=box];
    "Codebase audit / assessment" [shape=box];
    "Greenfield project kickoff" [shape=box];

    "Research Swarm" [shape=box style=filled fillcolor=lightyellow];
    "Epic Parallel Build" [shape=box style=filled fillcolor=lightyellow];
    "Sequential Pipeline" [shape=box style=filled fillcolor=lightyellow];
    "Parallel Sweep" [shape=box style=filled fillcolor=lightyellow];
    "Multi-Dimensional Audit" [shape=box style=filled fillcolor=lightyellow];
    "Full Lifecycle" [shape=box style=filled fillcolor=lightyellow];

    "What type of work?" -> "Research / knowledge gathering";
    "What type of work?" -> "Independent feature builds";
    "What type of work?" -> "Sequential dependent tasks";
    "What type of work?" -> "Same transformation across partitions";
    "What type of work?" -> "Codebase audit / assessment";
    "What type of work?" -> "Greenfield project kickoff";

    "Research / knowledge gathering" -> "Research Swarm";
    "Independent feature builds" -> "Epic Parallel Build";
    "Sequential dependent tasks" -> "Sequential Pipeline";
    "Same transformation across partitions" -> "Parallel Sweep";
    "Codebase audit / assessment" -> "Multi-Dimensional Audit";
    "Greenfield project kickoff" -> "Full Lifecycle";
}
Strategy When Agents Background Key Pattern
Research Swarm Knowledge gathering, docs, SOTA research 10-60+ Yes (100%) Fan-out, each writes own doc
Epic Parallel Build Plan with independent epics/features 20-60+ Yes (90%+) Wave dispatch by subsystem
Sequential Pipeline Dependent tasks, shared files 3-15 No (0%) Implement -> Review -> Fix chain
Parallel Sweep Same fix/transform across modules 4-10 No (0%) Partition by directory, fan-out
Multi-Dimensional Audit Quality gates, deep assessment 6-9 No (0%) Same code, different review lenses
Full Lifecycle New project from scratch All above Mixed Research -> Plan -> Build -> Review -> Harden

Strategy 1: Research Swarm

Mass-deploy background agents to build a knowledge corpus. Each agent researches one topic and writes one markdown document. Zero dependencies between agents.

When to Use

  • Kicking off a new project (need SOTA for all technologies)
  • Building a skill/plugin (need comprehensive domain knowledge)
  • Technology evaluation (compare multiple options in parallel)

The Pattern

Phase 1: Deploy research army (ALL BACKGROUND)
    Wave 1 (10-20 agents): Core technology research
    Wave 2 (10-20 agents): Specialized topics, integrations
    Wave 3 (5-10 agents): Gap-filling based on early results

Phase 2: Monitor and supplement
    - Check completed docs as they arrive
    - Identify gaps, deploy targeted follow-up agents
    - Read completed research to inform remaining dispatches

Phase 3: Synthesize
    - Read all research docs (foreground)
    - Create architecture plans, design docs
    - Use Plan agent to synthesize findings

Prompt Template: Research Agent

Research [TECHNOLOGY] for [PROJECT]'s [USE CASE].

Create a comprehensive research doc at [OUTPUT_PATH]/[filename].md covering:

1. Latest [TECH] version and features (search "[TECH] 2026" or "[TECH] latest")
2. [Specific feature relevant to project]
3. [Another relevant feature]
4. [Integration patterns with other stack components]
5. [Performance characteristics]
6. [Known gotchas and limitations]
7. [Best practices for production use]
8. [Code examples for key patterns]

Include code examples where possible. Use WebSearch and WebFetch to get current docs.

Key rules:

  • Every agent gets an explicit output file path (no ambiguity)
  • Include search hints: "search [TECH] 2026" (agents need recency guidance)
  • Numbered coverage list (8-12 items) scopes the research precisely
  • ALL agents run in background -- no dependencies between research topics

Dispatch Cadence

  • 3-4 seconds between agent dispatches
  • Group into thematic waves of 10-20 agents
  • 15-25 minute gaps between waves for gap analysis

Strategy 2: Epic Parallel Build

Deploy background agents to implement independent features/epics simultaneously. Each agent builds one feature in its own directory/module. No two agents touch the same files.

When to Use

  • Implementation plan with 10+ independent tasks
  • Monorepo with isolated packages/modules
  • Sprint backlog with non-overlapping features

The Pattern

Phase 1: Scout (FOREGROUND)
    - Deploy one Explore agent to map the codebase
    - Identify dependency chains and independent workstreams
    - Group tasks by subsystem to prevent file conflicts

Phase 2: Deploy build army (ALL BACKGROUND)
    Wave 1: Infrastructure/foundation (Redis, DB, auth)
    Wave 2: Backend APIs (each in own module directory)
    Wave 3: Frontend pages (each in own route directory)
    Wave 4: Integrations (MCP servers, external services)
    Wave 5: DevOps (CI, Docker, deployment)
    Wave 6: Bug fixes from review findings

Phase 3: Monitor and coordinate
    - Check git status for completed commits
    - Handle git index.lock contention (expected with 30+ agents)
    - Deploy remaining tasks as agents complete
    - Track via Sibyl tasks or TodoWrite

Phase 4: Review and harden (FOREGROUND)
    - Run Codex/code-reviewer on completed work
    - Dispatch fix agents for critical findings
    - Integration testing

Prompt Template: Feature Build Agent

**Task: [DESCRIPTIVE TITLE]** (task\_[ID])

Work in /path/to/project/[SPECIFIC_DIRECTORY]

## Context

[What already exists. Reference specific files, patterns, infrastructure.]
[e.g., "Redis is available at `app.state.redis`", "Follow pattern from `src/auth/`"]

## Your Job

1. Create `src/path/to/module/` with:
   - `file.py` -- [Description]
   - `routes.py` -- [Description]
   - `models.py` -- [Schema definitions]

2. Implementation requirements:
   [Detailed spec with code snippets, Pydantic models, API contracts]

3. Tests:
   - Create `tests/test_module.py`
   - Cover: [specific test scenarios]

4. Integration:
   - Wire into [main app entry point]
   - Register routes at [path]

## Git

Commit with message: "feat([module]): [description]"
Only stage files YOU created. Check `git status` before committing.
Do NOT stage files from other agents.

Key rules:

  • Every agent gets its own directory scope -- NO OVERLAP
  • Provide existing patterns to follow ("Follow pattern from X")
  • Include infrastructure context ("Redis available at X")
  • Explicit git hygiene instructions (critical with 30+ parallel agents)
  • Task IDs for traceability

Git Coordination for Parallel Agents

When running 10+ agents concurrently:

  1. Expect index.lock contention -- agents will retry automatically
  2. Each agent commits only its own files -- prompt must say this explicitly
  3. No agent should run git add . -- only specific files
  4. Monitor with git log --oneline -20 periodically
  5. No agent should push -- orchestrator handles push after integration

Strategy 3: Sequential Pipeline

Execute dependent tasks one at a time with review gates. Each task builds on the previous task's output. Use superpowers:subagent-driven-development for the full pipeline.

When to Use

  • Tasks that modify shared files
  • Integration boundary work (JNI bridges, auth chains)
  • Review-then-fix cycles where each fix depends on review findings
  • Complex features where implementation order matters

The Pattern

For each task:
    1. Dispatch implementer (FOREGROUND)
    2. Dispatch spec reviewer (FOREGROUND)
    3. Dispatch code quality reviewer (FOREGROUND)
    4. Fix any issues found
    5. Move to next task

Trust Gradient (adapt over time):
    Early tasks:  Implement -> Spec Review -> Code Review (full ceremony)
    Middle tasks: Implement -> Spec Review (lighter)
    Late tasks:   Implement only (pattern proven, high confidence)

Trust Gradient

As the session progresses and patterns prove reliable, progressively lighten review overhead:

Phase Review Overhead When
Full ceremony Implement + Spec Review + Code Review First 3-4 tasks
Standard Implement + Spec Review Tasks 5-8, or after patterns stabilize
Light Implement + quick spot-check Late tasks with established patterns
Cost-optimized Use model: "haiku" for reviews Formulaic review passes

This is NOT cutting corners -- it's earned confidence. If a late task deviates from the pattern, escalate back to full ceremony.


Strategy 4: Parallel Sweep

Apply the same transformation across partitioned areas of the codebase. Every agent does the same TYPE of work but on different FILES.

When to Use

  • Lint/format fixes across modules
  • Type annotation additions across packages
  • Test writing for multiple modules
  • Documentation updates across components
  • UI polish across pages

The Pattern

Phase 1: Analyze the scope
    - Run the tool (ruff, ty, etc.) to get full issue list
    - Auto-fix what you can
   
how to use orchestrate

How to use orchestrate 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 orchestrate
2

Execute installation command

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

$npx skills add https://github.com/hyperb1iss/hyperskills --skill orchestrate

The skills CLI fetches orchestrate from GitHub repository hyperb1iss/hyperskills 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/orchestrate

Reload or restart Cursor to activate orchestrate. Access the skill through slash commands (e.g., /orchestrate) 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.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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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

4.627 reviews
  • Mei Kapoor· Dec 28, 2024

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

  • Dhruvi Jain· Dec 12, 2024

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

  • Mei Thompson· Dec 12, 2024

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

  • Sophia Sanchez· Nov 19, 2024

    orchestrate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Nov 3, 2024

    Registry listing for orchestrate matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ganesh Mohane· Oct 22, 2024

    orchestrate reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kwame Kapoor· Oct 22, 2024

    orchestrate reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mei Sharma· Oct 10, 2024

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

  • Rahul Santra· Sep 13, 2024

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

  • Sophia Nasser· Sep 1, 2024

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

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