plan

A command that turns a feature request into an ordered list of development tasks, grouped into phases and linked by dependencies.

In plain words
What is it for?
Use it to inspect a project’s technologies, structure, patterns, and dependencies before planning a feature. It can also suggest a setup for a new project.
Why use it?
It removes the guesswork from deciding what to build first and how much detail each task needs. It also records checks that show when each task is complete.

Command

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/funkyoz/funkyoz-plugins/plan
Clone the repo
git clone --depth 1 https://github.com/FunkyOz/funkyoz-plugins
Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,083 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 $0.00013 $0.01083
Opus 5 $0.00006 $0.00541
Sonnet 5 $0.00003 $0.00217
Haiku 4.5 $0.00001 $0.00108

Measured yesterday against content hash 5706b48453c0, 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 — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

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.

software-engineer/commands/plan.md · 160 lines

How it starts

The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan Feature Command

You are a senior software engineer tasked with breaking down a feature request into well-structured, actionable tasks.

Input

The user wants to implement: {{1}}

Process

Step 1: Analyze the Project

First, analyze the current project to understand:

  1. Technology stack - What languages, frameworks, and tools are used?
  2. Project structure - How is the code organized?
  3. Existing patterns - What design patterns, coding conventions, and practices are already in use?
  4. Dependencies - What external libraries or services are used?

If this is an empty or new project:

  • Ask the user about their preferred technology stack
  • Recommend best practices for their chosen stack
  • Suggest a clean, maintainable project structure

Step 2: Break Down the Feature

Decompose the feature into logical tasks following these principles:

  1. Single Responsibility - Each task should have one clear objective
  2. Proper Sequencing - Tasks should be ordered by dependencies
  3. Appropriate Granularity - Not too large (hard to track), not too small (overhead)
  4. Testable Outcomes - Each task should have verifiable acceptance criteria

Step 3: Organize into Phases

Group related tasks into phases:

  • Foundation - Setup, configuration, base infrastructure
  • Core Implementation - Main functionality
  • Advanced Features - Optional enhancements
  • Testing - Unit tests, integration tests
  • Documentation - README, examples, API docs

Step 4: Create Task Files

Create a tasks/ directory in the project root with the following structure:

00-index.md

Create the main index file following this template:

# [Feature Name] - Task Index

This directory contains all implementation tasks for [feature description].

## Overview

**Total Tasks:** [count]
**Estimated Timeline:** [estimate]
**Current Status:** Planning Phase

---

## Phase N: [Phase Name] ([Priority] Priority)

[Phase description]

| # | Task | Priority | Complexity | Status | Dependencies |
|---|------|----------|------------|--------|--------------|
| XX | [Task Name](XX-task-slug.md) | [Priority] | [Complexity] | `todo` | [Deps] |

**Phase Duration:** [estimate]
**Deliverables:** [list]

---

[Repeat for each phase]

## Quick Reference

### Critical Path
[List minimum tasks for MVP]

### Task Status Legend
- `todo` - Not started
- `progress` - Currently being worked on
- `done` - Completed and tested

### Complexity Ratings
- **Low** - Straightforward implementation, ~1-2 days
- **Medium** - Moderate complexity, ~3-5 days
- **High** - Complex implementation, ~1-2 weeks

---

**Last Updated:** [date]
**Document Version:** 1.0

Read the full file on GitHub · 160 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. yesterday First seen · 160 lines · 13 tokens per session scan A 5706b48453c0

Subscribe to this mod's changes

plan is a command published in the GitHub repository FunkyOz/funkyoz-plugins (2 stars, last pushed 8mo ago), licensed MIT. It adds 13 tokens to every session and 1,083 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 2026-08-31.