plan-with-team

plan-with-team is a skill for Claude Code from jpoutrin/product-forge. It costs 39 tokens per session (6,773 once invoked), scanned A, original, MIT.

An engineering planning guide that creates an implementation plan and coordinates work between specialized team members. It is intended for multi-step development tasks with dependencies and parallel work.

In plain words
What is it for?
Use it to plan larger Django or Python projects, assign specialized implementation and validation work, and save the resulting specification document.
Why use it?
It helps turn a broad request into an organized blueprint so people can divide work, understand task order, and validate the result.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: model in frontmatter; reads .claude/ paths; mentions subagents.

Part of the team-orchestration plugin — 1 skill, 2 agents shipped together

Good fit Use it to plan larger Django or Python projects, assign specialized implementation and validation work, and save the resulting specification document.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jpoutrin/product-forge/plan-with-team
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.

Any agent
npx skills add jpoutrin/product-forge --skill plan-with-team
Clone the repo
git clone --depth 1 https://github.com/jpoutrin/product-forge

Made for: Claude Code.

Or install team-orchestration, the plugin that ships this one along with the rest of its 1 skill, 2 agents.

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-with-team

README.md
[![agentmods](https://agentmods.dev/badge/skills/jpoutrin/product-forge/plan-with-team/github.svg)](https://agentmods.dev/skills/jpoutrin/product-forge/plan-with-team)
Your own site
<a href="https://agentmods.dev/skills/jpoutrin/product-forge/plan-with-team"><img src="https://agentmods.dev/badge/skills/jpoutrin/product-forge/plan-with-team/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for plan-with-team

Your own site · 80×15
<a href="https://agentmods.dev/skills/jpoutrin/product-forge/plan-with-team"><img src="https://agentmods.dev/badge/skills/jpoutrin/product-forge/plan-with-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,773 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00039 $0.06773
Opus 5 $0.00019 $0.03386
Sonnet 5 $0.00008 $0.01355
Haiku 4.5 $0.00004 $0.00677

Measured 6d ago against content hash fa59f3666070, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

plan-with-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 6d 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.

plugins/team-orchestration/skills/plan-with-team/SKILL.md · 722 lines

How it starts

The opening of the file, as written. The whole thing — 722 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

Available Specialized Agents

Use these specialized agents for specific task types instead of defaulting to general-purpose:

Django Development

  • team-orchestration:django-builder - Fast Django implementation (models, views, serializers, admin)
  • team-orchestration:django-validator - Django validation (tests, type checks, linting)
  • python-experts:django-expert - Django development with best practices and modern patterns

Python Development

  • python-experts:fastapi-expert - FastAPI async API development
  • python-experts:celery-expert - Celery distributed task queues
  • python-experts:python-testing-expert - Python testing with pytest
  • python-experts:fastmcp-expert - FastMCP Python server development

Frontend Development

  • frontend-experts:react-typescript-expert - React TypeScript components
  • frontend-experts:playwright-testing-expert - Playwright E2E testing
  • typescript-experts:fastmcp-ts-expert - FastMCP TypeScript servers

DevOps & Infrastructure

  • devops-data:devops-expert - CI/CD, infrastructure, Docker, Kubernetes
  • devops-data:data-engineering-expert - Data pipelines, dbt, SQLMesh
  • devops-data:cto-architect - System architecture and technical decisions

Security & Compliance

  • security-compliance:mcp-security-expert - MCP security and authorization
  • security-compliance:dpo-expert - GDPR, CCPA, privacy compliance

Read the full file on GitHub · 722 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. 6d ago First seen · 722 lines · 0 tokens per session scan A fa59f3666070

Subscribe to this mod's changes

plan-with-team is a skill published in the GitHub repository jpoutrin/product-forge (16 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 6,773 once invoked, about $0.0002 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 2026-09-03.

Related

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