team-plan

team-plan is a skill for Claude Code from parisgroup-ai/imersao-ia-setup. It costs 62 tokens per session (3,186 once invoked), scanned A, original, MIT.

A planning workflow that uses several research agents in parallel to turn a feature request into an implementation plan. It gathers codebase context and requirements, then combines them into a plan for later execution.

In plain words
What is it for?
Use it to plan small, medium, or large features before implementation, especially when you want parallel research and a plan that can feed later task or execution workflows.
Why use it?
It reduces the time spent investigating a large feature before coding begins. A shared plan can reveal missing requirements and break work into clearer steps.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the imersao plugin — 74 skills, 7 commands shipped together

Good fit Use it to plan small, medium, or large features before implementation, especially when you want parallel research and a plan that can feed later task or execution workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parisgroup-ai/imersao-ia-setup/team-plan
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 parisgroup-ai/imersao-ia-setup --skill team-plan
Clone the repo
git clone --depth 1 https://github.com/parisgroup-ai/imersao-ia-setup

Made for: Claude Code.

Or install imersao, the plugin that ships this one along with the rest of its 74 skills, 7 commands.

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 team-plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/team-plan/github.svg)](https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/team-plan)
Your own site
<a href="https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/team-plan"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/team-plan/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 team-plan

Your own site · 80×15
<a href="https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/team-plan"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/team-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,186 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 $0.00062 $0.03186
Opus 5.5 $0.00025 $0.01274
Sonnet 5.5 $0.00012 $0.00637
Haiku 4.5 $0.00006 $0.00319

Measured 21d ago against content hash 821a42d17f8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

team-plan 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 21d 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/imersao/skills/team-plan/SKILL.md · 457 lines

How it starts

The opening of the file, as written. The whole thing — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Team Plan

Scatter-gather planning team. Spawns research agents in parallel, gathers codebase context and requirements analysis, consolidates into an implementation plan compatible with /team-execute and /plan-to-tasks.

Usage

/team-plan "Add badge system for students"              # Default scope (medium)
/team-plan "Add badge system" --scope large             # Full research (3 agents)
/team-plan "Fix login redirect" --scope small           # Quick plan (1 agent)
/team-plan "Add badge system" --output my-badges        # Custom output filename

Parse Arguments

Extract from: {{ARGUMENTS}}

FEATURE = quoted string or remaining text after flags
SCOPE   = small | medium | large (default: medium)
OUTPUT  = --output value or auto-generated from FEATURE

If no arguments or FEATURE is empty, show help and stop:

/team-plan - Create implementation plans with parallel research agents

Usage:
  /team-plan "Add user badges"                    Medium scope (2 agents)
  /team-plan "Add badges" --scope large           Full research (3 agents)
  /team-plan "Fix redirect" --scope small         Quick plan (1 agent)
  /team-plan "Add badges" --output badge-plan     Custom filename

Pipeline: RESEARCH (parallel) → CONSOLIDATE → OUTPUT
Agents:   researcher + analyst [+ ux-mapper]
Output:   .claude/plans/{date}-{slug}.md

Next steps after plan:
  /team-execute <plan>           Execute with agent team
  /plan-to-tasks import <plan>   Import to TaskNotes

Phase 1: PREPARE

Generate Plan Metadata

SLUG      = slugify(FEATURE)        # e.g., "add-badge-system"
DATE      = YYYY-MM-DD              # today
PLAN_PATH = .claude/plans/{DATE}-{OUTPUT or SLUG}.md

Verify .claude/plans/ directory exists (create if not).


Phase 2: SCATTER (Spawn Research Agents)

Agent Selection

If SCOPE = small:
  agents = [researcher]                           # 1 agent
If SCOPE = medium:
  agents = [researcher, analyst]                  # 2 agents
If SCOPE = large:
  agents = [researcher, analyst, ux-mapper]       # 3 agents

Read the full file on GitHub · 457 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. 21d ago First seen · 457 lines · 62 tokens per session scan A 821a42d17f8c

Subscribe to this mod's changes

team-plan is a skill published in the GitHub repository parisgroup-ai/imersao-ia-setup (1 stars, last pushed 20d ago), licensed MIT. It adds 62 tokens to every session and 3,186 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-06.

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