plan_w_team

plan_w_team is a command for Claude Code from disler/pi-vs-claude-code. It costs 16 tokens per session (3,115 once invoked), scanned A, original, MIT.

A planning command that turns a user's requirements into a detailed engineering plan saved as a Markdown file in a specs directory.

In plain words
What is it for?
Use it to break down a chore, feature, refactor, fix, or enhancement into an implementation blueprint, with optional guidance for assigning work and ordering dependencies.
Why use it?
It separates deciding how to build something from writing the code, so the work can be reviewed before implementation begins.

Command for Claude Code

About the project

pi-vs-claude-code is a collection of customized Pi Coding Agent instances used to compare an open-source coding agent with Claude Code. It is for exploring agent interfaces, orchestration, safety auditing, and integrations between coding agents. The catalogue entries are examples of the customized agent workflows in the collection.

disler/pi-vs-claude-code · 1,662 stars · on GitHub

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/disler/pi-vs-claude-code/plan_w_team
Clone the repo
git clone --depth 1 https://github.com/disler/pi-vs-claude-code

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for plan_w_team

README.md
[![agentmods](https://agentmods.dev/badge/commands/disler/pi-vs-claude-code/plan_w_team.svg)](https://agentmods.dev/commands/disler/pi-vs-claude-code/plan_w_team)
Your own site
<a href="https://agentmods.dev/commands/disler/pi-vs-claude-code/plan_w_team"><img src="https://agentmods.dev/badge/commands/disler/pi-vs-claude-code/plan_w_team.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,115 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 $0.00016 $0.03115
Opus 5 $0.00008 $0.01558
Sonnet 5 $0.00003 $0.00623
Haiku 4.5 $0.00002 $0.00312

Measured 5d ago against content hash 19e4a66345f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plan_w_team scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.claude/commands/plan_w_team.md · 351 lines

How it starts

The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan With Team

Create a detailed implementation plan based on the user's requirements provided through the USER_PROMPT variable. Analyze the request, think through the implementation approach, and save a comprehensive specification document to PLAN_OUTPUT_DIRECTORY/<name-of-plan>.md that can be used as a blueprint for actual development work. Follow the Instructions and work through the Workflow to create the plan.

Variables

USER_PROMPT: $1 ORCHESTRATION_PROMPT: $2 - (Optional) Guidance for team assembly, task structure, and execution strategy PLAN_OUTPUT_DIRECTORY: specs/ TEAM_MEMBERS: .claude/agents/team/*.md GENERAL_PURPOSE_AGENT: general-purpose

Instructions

  • PLANNING ONLY: Do NOT build, write code, or deploy agents. Your only output is a plan document saved to PLAN_OUTPUT_DIRECTORY.
  • If no USER_PROMPT is provided, stop and ask the user to provide it.
  • If ORCHESTRATION_PROMPT is provided, use it to guide team composition, task granularity, dependency structure, and parallel/sequential decisions.
  • Carefully analyze the user's requirements provided in the USER_PROMPT variable
  • Determine the task type (chore|feature|refactor|fix|enhancement) and complexity (simple|medium|complex)
  • Think deeply (ultrathink) about the best approach to implement the requested functionality or solve the problem
  • Understand the codebase directly without subagents to understand existing patterns and architecture
  • Follow the Plan Format below to create a comprehensive implementation plan
  • Include all required sections and conditional sections based on task type and complexity
  • Generate a descriptive, kebab-case filename based on the main topic of the plan
  • Save the complete implementation plan to PLAN_OUTPUT_DIRECTORY/<descriptive-name>.md
  • Ensure the plan is detailed enough that another developer could follow it to implement the solution
  • Include code examples or pseudo-code where appropriate to clarify complex concepts
  • Consider edge cases, error handling, and scalability concerns
  • Understand your role as the team lead. Refer to the Team Orchestration section for more details.

Read the full file on GitHub · 351 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. 5d ago First seen · 351 lines · 0 tokens per session scan A 19e4a66345f0

Subscribe to this mod's changes

plan_w_team is a command published in the GitHub repository disler/pi-vs-claude-code (1,662 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 3,115 once invoked, about $0.0001 per session on Opus 5. 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.