Best use case
Intervention Orchestrator Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Purpose
Teams using Intervention Orchestrator Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/orchestrator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Intervention Orchestrator Skill Compares
| Feature / Agent | Intervention Orchestrator Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Purpose
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Intervention Orchestrator Skill ## Purpose Coordinate and execute intervention strategies during CFN Loop execution. ## Intervention Types 1. Agent Swap 2. Specialist Injection 3. Scope Simplification ## Workflow 1. Receive intervention trigger 2. Analyze current loop context 3. Select appropriate intervention strategy 4. Generate actionable recommendations 5. Prepare configuration for next iteration ## Usage ```bash ./execute-intervention.sh \ --trigger "confidence_plateau" \ --iteration 3 \ --loop3-agents "backend-dev,coder" \ --feedback-themes "security" ``` ## Output Components - Intervention type - Updated agent configuration - Context injection guidance - Expected improvement projection ## Decision Flow - Validate intervention trigger - Consult specialized skills (swap, injection, simplifier) - Generate holistic intervention strategy - Minimize disruptive changes ## Best Practices - Transparent decision process - Minimal side effects - Continuous improvement focus - Preserve team cohesion
Related Skills
Intervention Detector Skill
## Purpose
cfn-intervention-system
Human intervention detection and orchestration for CFN Loop. Use when automated processes need human oversight, when escalation is required, or when managing intervention workflows and approval gates.
supabase-schema-sync
Introspects Supabase DB after migrations and updates project db-query skill with current schema. Run after any migration to keep agent context accurate.
commit
Stage, commit, and push changes using a background github-commit-agent. Accepts optional args for message override or push control.
cfn-vote-implement
MUST BE USED after cfn-dry-review or cfn-alpha-launch:manifest produces a manifest. Also the verification phase of /cfn-loop-task. Do not manually implement code review suggestions - always route through this skill. 3-agent specialized voting. Unanimous (3/3) auto-implemented with TDD. 2/3 routed to product-owner agent. 1/3 surfaced to user via AskUserQuestion (batched 4 per call, at end).
cfn-utilities
Reusable bash utility functions for CFN Loop - logging, error handling, retry, file operations. Use when you need structured logging, atomic file operations, retry logic with exponential backoff, or standardized error handling in bash scripts.
CFN Test Runner Skill
**Version:** 1.0.0
cfn-test-framework
Test execution, running, and webapp testing for CFN
cfn-task-planning
Classify tasks, initialize structured configs with scope boundaries, decompose complex tasks
Specialist Injection Skill
## Purpose
!/bin/bash
# cfn-task-intelligence.sh
Task Complexity Estimator
**Version:** 1.0.0