plan

plan is a command for Claude Code from jwynia/context-networks. It costs 0 tokens per session (1,916 once invoked), scanned A, original, MIT.

A planning-only command for understanding a software problem and designing a solution before implementation begins.

In plain words
What is it for?
Exploring an existing codebase, reviewing prior decisions, gathering functional and security requirements, researching options, and documenting an implementation plan.
Why use it?
It prevents premature coding by requiring research, requirements, dependencies, risks, architecture decisions, and task breakdowns first.

Command for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/jwynia/context-networks/plan
Clone the repo
git clone --depth 1 https://github.com/jwynia/context-networks

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,916 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01916
Opus 5 $0.00000 $0.00958
Sonnet 5 $0.00000 $0.00383
Haiku 4.5 $0.00000 $0.00192

Measured 3d ago against content hash 0e2ac263b12f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plan scanned grade A with 0 findings against 26 rules in 11 categories โ€” prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency โ€” measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/commands/plan.md ยท 307 lines

How it starts

The opening of the file, as written. The whole thing โ€” 307 lines โ€” stays where its author put it; the contents beside it link to each section on GitHub.

Planning & Architecture Mode

๐Ÿšซ Implementation Restrictions

THIS IS A PLANNING-ONLY COMMAND

You are now in Planning & Architecture Mode for: $ARGUMENTS

In this mode, you MUST:

  • โœ… Research and understand the problem space
  • โœ… Document findings in the context network
  • โœ… Design architecture and patterns
  • โœ… Create task breakdowns
  • โœ… Identify dependencies and risks

You MUST NOT:

  • โŒ Write implementation code
  • โŒ Create files outside context-network/
  • โŒ Modify existing code
  • โŒ Run build or deployment commands
  • โŒ Make configuration changes

Planning Process

Phase 1: Problem Understanding ๐Ÿ”

  1. Define the Problem

    • What are we trying to solve?
    • Why does this matter?
    • Who are the stakeholders?
    • What are the success criteria?
  2. Explore the Current State

    • Search existing codebase for related functionality
    • Check context network for prior decisions
    • Identify what already exists
    • Document current limitations
  3. Gather Requirements

    • Functional requirements
    • Non-functional requirements (performance, security, etc.)
    • Constraints and boundaries
    • Assumptions to validate

Phase 2: Research & Discovery ๐Ÿ”ฌ

  1. Research Existing Solutions

    • Industry patterns and best practices
    • Similar implementations in the codebase
    • External libraries or frameworks
    • Academic or theoretical foundations
  2. Technology Evaluation

    • Available tools and technologies
    • Compatibility with existing stack
    • Learning curve and team expertise
    • Long-term maintenance implications
  3. Document Findings

    context-network/research/$ARGUMENTS/
    โ”œโ”€โ”€ overview.md           # Problem and research summary
    โ”œโ”€โ”€ findings.md          # Detailed discoveries
    โ”œโ”€โ”€ alternatives.md      # Options considered
    โ””โ”€โ”€ recommendations.md   # Suggested approach
    

Phase 3: Architecture Design ๐Ÿ“

  1. High-Level Design
    • System boundaries and interfaces
    • Component relationships
    • Data flow diagrams
    • Sequence diagrams for key scenarios

Read the full file on GitHub ยท 307 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen ยท 307 lines ยท 0 tokens per session scan A 0e2ac263b12f

Subscribe to this mod's changes

plan is a command published in the GitHub repository jwynia/context-networks (24 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,916 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.