cmd-feature-dev

cmd-feature-dev is a cursor rule for Cursor from nota-america/forgecat-agent-profiles. It costs 1,060 tokens per session, scanned A, original, Apache-2.0.

Guided feature development with codebase understanding and architecture focus.

Cursor rule for Cursor

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 rules/nota-america/forgecat-agent-profiles/cmd-feature-dev
Clone the repo
git clone --depth 1 https://github.com/nota-america/forgecat-agent-profiles

Made for: Cursor.

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 cmd-feature-dev

README.md
[![agentmods](https://agentmods.dev/badge/rules/nota-america/forgecat-agent-profiles/cmd-feature-dev.svg)](https://agentmods.dev/rules/nota-america/forgecat-agent-profiles/cmd-feature-dev)
Your own site
<a href="https://agentmods.dev/rules/nota-america/forgecat-agent-profiles/cmd-feature-dev"><img src="https://agentmods.dev/badge/rules/nota-america/forgecat-agent-profiles/cmd-feature-dev.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,060 This file is loaded in full into every session.
When invoked 1,060 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.01060 $0.01060
Opus 5 $0.00530 $0.00530
Sonnet 5 $0.00212 $0.00212
Haiku 4.5 $0.00106 $0.00106

Measured today against content hash d2e0db0bc113, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cmd-feature-dev 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 today.

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.

profiles/anthropics/claude-plugins-official/anthropics_claude-plugins-official_feature-dev/for-cursor/.cursor/rules/cmd-feature-dev.mdc · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Development

You are helping a developer implement a new feature. Follow a systematic approach: understand the codebase deeply, identify and ask about all underspecified details, design elegant architectures, then implement.

Core Principles

  • Ask clarifying questions: Identify all ambiguities, edge cases, and underspecified behaviors. Ask specific, concrete questions rather than making assumptions. Wait for user answers before proceeding with implementation. Ask questions early (after understanding the codebase, before designing architecture).
  • Understand before acting: Read and comprehend existing code patterns first
  • Read files identified by agents: When launching agents, ask them to return lists of the most important files to read. After agents complete, read those files to build detailed context before proceeding.
  • Simple and elegant: Prioritize readable, maintainable, architecturally sound code
  • Use TodoWrite: Track all progress throughout

Phase 1: Discovery

Goal: Understand what needs to be built

Initial request: $ARGUMENTS

Actions:

  1. Create todo list with all phases
  2. If feature unclear, ask user for:
    • What problem are they solving?
    • What should the feature do?
    • Any constraints or requirements?
  3. Summarize understanding and confirm with user

Phase 2: Codebase Exploration

Goal: Understand relevant existing code and patterns at both high and low levels

Actions:

  1. Launch 2-3 code-explorer agents in parallel. Each agent should:

    • Trace through the code comprehensively and focus on getting a comprehensive understanding of abstractions, architecture and flow of control
    • Target a different aspect of the codebase (eg. similar features, high level understanding, architectural understanding, user experience, etc)
    • Include a list of 5-10 key files to read

    Example agent prompts:

    • "Find features similar to [feature] and trace through their implementation comprehensively"
    • "Map the architecture and abstractions for [feature area], tracing through the code comprehensively"
    • "Analyze the current implementation of [existing feature/area], tracing through the code comprehensively"
    • "Identify UI patterns, testing approaches, or extension points relevant to [feature]"

Read the full file on GitHub · 126 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. today First seen · 126 lines · 1,060 tokens per session scan A d2e0db0bc113

Subscribe to this mod's changes

cmd-feature-dev is a cursor rule published in the GitHub repository nota-america/forgecat-agent-profiles (63 stars, last pushed today), licensed Apache-2.0. It adds 1,060 tokens to every session, about $0.0053 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.