create_plan_nt

A command that creates a detailed software implementation plan through research and discussion, without requiring a thoughts directory. It can start from a task description, ticket, or file.

In plain words
What is it for?
Use it to investigate a task, review related research or previous work, and agree on the files, changes, and approach needed to implement it.
Why use it?
It turns incomplete requirements and scattered context into a reviewed technical plan before coding begins.

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/jeffh/claude-plugins/create_plan_nt
Clone the repo
git clone --depth 1 https://github.com/jeffh/claude-plugins
Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,158 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin 95% copy Near-identical to another mod 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 $0.00011 $0.03158
Opus 5 $0.00005 $0.01579
Sonnet 5 $0.00002 $0.00632
Haiku 4.5 $0.00001 $0.00316

Measured 2d ago against content hash 21f0758cf4d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create_plan_nt scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- [ ] API endpoint returns 200: `curl localhost:8080/api/new-endpoint`
Origin

This is a copy

95% identical to create_plan — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

humanlayer/commands/create_plan_nt.md · 440 lines

How it starts

The opening of the file, as written. The whole thing — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementation Plan

You are tasked with creating detailed implementation plans through an interactive, iterative process. You should be skeptical, thorough, and work collaboratively with the user to produce high-quality technical specifications.

Initial Response

When this command is invoked:

  1. Check if parameters were provided:

    • If a file path or ticket reference was provided as a parameter, skip the default message
    • Immediately read any provided files FULLY
    • Begin the research process
  2. If no parameters provided, respond with:

I'll help you create a detailed implementation plan. Let me start by understanding what we're building.

Please provide:
1. The task/ticket description (or reference to a ticket file)
2. Any relevant context, constraints, or specific requirements
3. Links to related research or previous implementations

I'll analyze this information and work with you to create a comprehensive plan.

Tip: You can also invoke this command with a ticket file directly: `/create_plan thoughts/shared/tickets/eng_1234.md`
For deeper analysis, try: `/create_plan think deeply about thoughts/shared/tickets/eng_1234.md`

Then wait for the user's input.

Process Steps

Step 1: Context Gathering & Initial Analysis

  1. Read all mentioned files immediately and FULLY:

    • Ticket files (e.g., thoughts/shared/tickets/eng_1234.md)
    • Research documents
    • Related implementation plans
    • Any JSON/data files mentioned
    • IMPORTANT: Use the Read tool WITHOUT limit/offset parameters to read entire files
    • CRITICAL: DO NOT spawn sub-tasks before reading these files yourself in the main context
    • NEVER read files partially - if a file is mentioned, read it completely
  2. Spawn initial research tasks to gather context: Before asking the user any questions, use specialized agents to research in parallel:

    • Use the codebase-locator agent to find all files related to the ticket/task
    • Use the codebase-analyzer agent to understand how the current implementation works
    • If a Linear ticket is mentioned, use the linear-ticket-reader agent to get full details

Read the full file on GitHub · 440 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. 2d ago First seen · 440 lines · 11 tokens per session scan A 21f0758cf4d9

Subscribe to this mod's changes

create_plan_nt is a command published in the GitHub repository jeffh/claude-plugins (12 stars, last pushed 18d ago), licensed Apache-2.0. It adds 11 tokens to every session and 3,158 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to create_plan, differing in 24 lines, and is treated as a copy.