From rcc
Plans agent system components to create/modify/delete from analysis reports and workflows: designs DOT architecture flowcharts using Anthropic patterns, checks reuse, gets user confirmation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/rcc:planning-agent-systemsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Planning agent systems IS mapping workflows to components with explicit rationale.**
Planning agent systems IS mapping workflows to components with explicit rationale.
Read the analysis report and workflow summary, decide what to create/modify/delete, identify which writing-* skills to invoke, and get user confirmation before execution.
Core principle: Every component must trace back to a workflow need or a weakness fix. No speculative components.
Violating the letter of the rules is violating the spirit of the rules.
Pattern: Chain
Handoff: user-confirmation
Next: applying-agent-systems
Chain: main
Before ANY action, create task list using TaskCreate:
TaskCreate for EACH task below:
- Subject: "[planning-agent-systems] Task N: <action>"
- ActiveForm: "<doing action>"
Tasks:
Announce: "Created 5 tasks. Starting execution..."
Execution rules:
TaskUpdate status="in_progress" BEFORE starting each taskTaskUpdate status="completed" ONLY after verification passesTaskList to confirm all completedGoal: Load analysis report (if available) and workflow summary.
Read:
docs/agent-system/*-analysis.md (most recent, if exists)docs/agent-system/*-workflows.md (most recent)Extract:
Verification: Have a clear list of requirements from both sources.
Goal: Visualize the entire agent system topology before deciding individual components.
Why this comes first: Component lists hide dependency gaps and workflow disconnects. A flowchart forces you to see the whole picture — entry points, decision branches, data flow, and handoff points — before committing to any component.
CRITICAL: Read references/anthropic-patterns.md for the six Anthropic workflow patterns, DOT flowchart conventions, and dependency graph template.
Step 1 — Classify workflows into Anthropic patterns using the reference table.
Step 2 — Draw the architecture flowchart in DOT format using the reference conventions.
Step 3 — Build the dependency graph from the flowchart, assigning phases by dependency depth.
Step 4 — Identify the simplest viable subset:
Ask: "What is the minimum set of components that delivers value?"
Verification: Architecture flowchart produced showing all workflows, patterns identified, dependency graph built, phases assigned.
Goal: Decide action for each component type.
CRITICAL: Read references/component-planning.md for the evaluation table, decision criteria, size constraints, and writing skill assignments.
Use the dependency graph from Task 2 to determine execution order. Do NOT use a fixed order — let dependencies drive sequencing. Components in the same phase with no mutual dependencies can be built in parallel.
Verification: Each planned component has a traced rationale and assigned writing-* skill. No conflicts identified.
Goal: Write structured plan to docs/agent-system/{timestamp}-plan.md.
CRITICAL: Read references/plan-template.md for the full plan format including architecture flowchart, pattern mapping, dependency graph, and component sections.
Verification: Plan written with complete execution order and traceability.
Goal: Present plan and get explicit approval.
Present the FULL plan to user. Show: architecture flowchart, pattern mapping, dependency graph with phases, each component's purpose and content, weakness fixes, core/enhancement classification, and estimated scope per phase.
Anti-pattern: Listing component names without explaining what they do is NOT presenting.
Ask: "這個計畫看起來可以嗎?要開始建立元件嗎?"
Handoff: After user confirms → invoke applying-agent-systems skill, pass plan path
Verification: User has reviewed the full plan and explicitly approved.
These thoughts mean you're rationalizing. STOP and reconsider:
| Thought | Reality |
|---|---|
| "Skip the flowchart" | Component lists hide dependency gaps. The flowchart reveals what's missing. |
| "Create everything" | YAGNI. Only create what traces to a need. |
| "Skip traceability" | Untraceable components become mystery debt. |
| "Skip confirmation" | User approval prevents wasted effort. |
| "Skip reuse check" | Duplicating existing skills creates conflicts. |
| "One big rule" | Multiple focused rules > one bloated rule. |
| "Fixed order is fine" | Dependencies vary per project. Let the graph decide. |
digraph plan_agent {
rankdir=TB;
start [label="Plan agent\nsystem", shape=doublecircle];
read [label="Task 1: Read\ninputs", shape=box];
flowchart [label="Task 2: Design\narchitecture flowchart", shape=box, style=filled, fillcolor="#ffffcc"];
plan [label="Task 3: Plan\ncomponents", shape=box];
produce [label="Task 4: Produce\ncomponent plan", shape=box];
confirm [label="Task 5: User\nconfirmation", shape=box];
approved [label="Approved?", shape=diamond];
handoff [label="Invoke\napplying-agent-systems", shape=box];
done [label="Planning complete", shape=doublecircle];
start -> read;
read -> flowchart;
flowchart -> plan;
plan -> produce;
produce -> confirm;
confirm -> approved;
approved -> handoff [label="yes"];
approved -> flowchart [label="no\nrevise"];
handoff -> done;
}
npx claudepluginhub wayne930242/reflexive-claude-codeOrchestrates agent system component creation by sequentially invoking writing-claude-md, writing-rules, writing-hooks, writing-skills, and writing-subagents from a plan. Use after plan confirmation or on 'apply agent plan'.
Designs multi-step agentic workflows with analyze-plan-validate-execute-verify to prevent irreversible mistakes in LLM agents.
Designs AI agent workflows using Meta's 9-step process and 8-layer architecture. Guides scope definition, input/output structuring, tool integration for agentic solutions.