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Orchestration

Skill namos2502/CortexLink/skills/orchestration

A simple plugin for CLI AI agents to stream lining cross-agent workflows

Install
npx -y skills add namos2502/CortexLink --skill orchestration

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This skill should be used when a multi-step task can benefit from parallel subtask execution or cross-CLI delegation — decomposing work into independent subtasks, routing them to native subagents or CLI agents in parallel, and synthesizing their structured reports back to the user.

SKILL.md

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CortexLink Orchestration

Overview

CortexLink turns your active AI agent into a control center that fans out tasks to peer CLI agents. Each agent executes in isolation, self-verifies, and returns a structured report. You stay in context — results come back, intermediate noise stays out.

Core principle: Delegate with a clear reason. Review every report before proceeding.

Violating the letter of this protocol is violating its spirit.

The Iron Law

NO CROSS-CLI DELEGATION WITHOUT A CLEAR REASON.
NO PROCEEDING WITHOUT REVIEWING THE REPORT.
ONE AGENT PER SUBTASK — never delegate the same subtask to more than one agent.
INDEPENDENT SUBTASKS RUN IN PARALLEL — never serialize by default.
PREFER NATIVE SUBAGENTS — cross-CLI only when platform-specific or context isolation is needed.
Claude Code → native Agent tool first → Copilot CLI (GitHub) → Claude CLI (last resort).
Copilot CLI → Claude CLI.

The Two-Tier Model

CONTROL CENTER (your AI agent — decomposes, routes, reviews)
  ├── NATIVE SUBAGENT (Agent tool — preferred for all general tasks)
  ├── AGENT (Copilot CLI — GitHub/platform-specific tasks only)
  ├── AGENT (Claude CLI — last resort: Anthropic-specific model or context isolation)
  └── AGENT (future-cli ...)
        └── [own tools & sub-agents — internal, platform-native]

The control center IS your active AI agent — it holds the plan and directs the work. Native subagents (Agent tool) are the first choice: no auth, no process overhead, full tool access. Cross-CLI agents are full CLI agents in their own right — not dumb executors — but are for platform-specific work only. The tree is one level deep: agents are peers, they don't chain to each other. Width scales as you add agents; depth stays fixed.

Task Complexity

Classify every task before routing. This determines how much spec detail to write and whether a Q&A phase is needed.

LevelSignalsDelegation style
SimpleSingle operation, read-only, unambiguous outputHandle inline — no cross-CLI
Standard2–4 operations, may write, clear success criteria, low rework costFull spec: problem + acceptance criteria
Complex5+ operations, writes/commits/PRs, judgment calls, OR high rework costFull spec + Q&A turn before execution

Key signal for Complex: rework cost. Tasks with irreversible steps (PRs, commits, deploys) or required judgment calls always qualify.

Concurrency First

After decomposing, map dependencies before dispatching. Default to parallel — serialize only when a subtask needs another's output.

  • Parallel: no shared state, no output dependency → dispatch all in one batched message
  • Sequential: subtask B consumes A's report → block on A first, then dispatch B

Serializing independent subtasks doubles wall-clock time for no gain. When background agents are running, do prep work for synthesis — never idle-block.

Concurrency Primitives

PrimitiveHowUse for
Multiple Agent calls in one messageEmit N Agent tool calls in a single responsePrimary parallel fan-out — native subagents
Agent + run_in_background: trueSet on the Agent tool callLong-running native subagent; collect via Read on output file
Shell cmd1 & cmd2 & wait in BashStandard shell backgrounding, write to temp filescopilot -p / claude -p fan-out only

run_in_background: true is a parameter of the Agent tool, not the Bash tool.

Preferred order for subtasks:

  1. Native Agent tool — no auth, no process overhead, preferred for all general work
  2. copilot -p — GitHub/platform-specific tasks only
  3. claude -p — Anthropic-specific model or context isolation only

When to Delegate Cross-CLI

Each subtask goes to exactly ONE agent — the decision tree picks which one, then stop. Never route the same subtask to both agents simultaneously.

Peer direction by host:

  • Claude Code → Copilot CLI for GitHub tasks; Claude CLI only as last resort (when context isolation or a specific Anthropic model is needed AND native tools are insufficient)
  • Copilot CLI → Claude CLI for code tasks, analysis, and refactors

Delegate when:

  1. Platform-specific — GitHub ops (PRs, repos, Actions) → Copilot; Anthropic reasoning or Claude-specific model → Claude CLI
  2. Context isolation — offload a long subtask so its intermediate work never enters your context
  3. Different model needed — the target CLI runs a model the host cannot
  4. Task is Standard or Complex — the work inside the agent justifies the delegation overhead

Do NOT delegate when:

  1. Task needs your current session context, open files, or in-memory state
  2. The host has a native subagent that can handle it — always try native Agent first
  3. The target CLI is not installed or not authenticated
  4. You have no clear reason — "big task" is not a reason
  5. Task is Simple — handle inline; a full agent session costs more than the task itself

Decision tree:

New task →
  Simple? → handle inline (no cross-CLI)
  Host native subagent available? → use it (faster, no auth needed)
  Platform-specific (GitHub, Anthropic API, etc.)? → cross-CLI
  Context isolation needed (verbose output, long subtask)? → cross-CLI
  Different model needed? → cross-CLI
  Default → handle inline

  When going cross-CLI:
    Standard → full spec (problem + acceptance criteria)
    Complex → full spec + Q&A turn before execution

Control Center Protocol

  1. Decompose — Break into scoped, independently executable subtasks. Each must be verifiable by the agent itself. After decomposing, identify which subtasks are independent — these are your parallel batch.
  2. Route — Apply decision tree. Prefer native Agent tool. Check CLI agent availability only if cross-CLI is needed (see references/report-format.md).
  3. Dispatch — Batch all independent subtasks into ONE message. For native subagents: emit multiple Agent tool calls in one response. For cross-CLI: background with shell & in a single Bash call, write output to temp files. Use delegation prompt template for cross-CLI (see references/delegation-template.md); always include scope, success criteria, and report format. Each subtask goes to ONE agent — never dispatch the same work to two agents.
  4. Useful-wait — While background agents run, do prep work for synthesis or the next subtask. Never idle-block when there is useful work to do.
  5. Review — Read STATUS first. Spot-check if needed (git diff, tests). Decide: proceed, re-assign, or adjust.
  6. Track — Update state (done / pending / failed). Never skip to the next subtask without reviewing the current report.
  7. Synthesize — Consolidate into one output for the user. Lead with issues (🔴 blocker / 🟠 should fix / 🟡 minor), then a one-sentence verdict. If any subtask is ❌, hold the verdict until resolved.

Red Flags — STOP

  • Delegating without a clear reason ("it's a big task")
  • Moving to the next subtask without reading the report
  • Returning raw output instead of a structured report
  • Marking ✅ without running verification
  • Retrying a ❌ task without reading ISSUES first
  • Delegating a task that needs current session context
  • Agents chaining to each other (all coordination goes through the control center)
  • Delegating the same subtask to more than one agent (one subtask → one agent, always)
  • Opening an interactive terminal session for delegation (always use the -p prompt flag)
  • Reaching for copilot -p / claude -p when a native Agent tool call would do
  • Dispatching agents one at a time when subtasks are independent (serializing for no reason)
  • Idle-blocking on agent output when there is useful prep work to do

Green Flags — Do These

  • ≥2 independent subtasks → batch all into one message, dispatch simultaneously
  • General code task → native Agent tool first, not Claude CLI
  • Background agent running → do prep work, don't idle-block
  • Native Agent can handle it → skip cross-CLI entirely

Quick Reference

I want to…Do this
Run independent subtasks in parallelMultiple Agent tool calls in one message
Long-running background native workAgent + run_in_background: true; collect via Read
GitHub taskCopilot — load cortexlink:copilot-cli via the Skill tool
General code task (native first)Native Agent tool — emit multiple Agent calls in one message
General code task (cross-CLI)Claude CLI — load cortexlink:claude-cli (last resort only)
Delegation promptSee references/delegation-template.md
Report format / self-verifySee references/report-format.md
Agent context protocolSee references/agent-context.md
Add a new agentDrop skills/agents/<name>/SKILL.md — follow existing format
Handle auth failureTell user: /cortexlink:setup
Handle ❌ reportRead ISSUES. Re-assign or handle natively. Never retry blindly.

What ships with it: 3 files

5.7 KB alongside SKILL.md

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