feature

An end-to-end feature-building workflow that takes an idea through planning, implementation, testing, and final checks. It uses separate software agents to design the work, write code and tests, and check for errors and security problems.

In plain words
What is it for?
Use it to add a new feature from a description, such as authentication, while producing a plan, implementation, tests, and validation results.
Why use it?
Building a feature usually requires coordinating requirements, code, tests, and review. This puts those stages into one process with checks before the work is finished.

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/nxtg-ai/forge-plugin/feature
Clone the repo
git clone --depth 1 https://github.com/nxtg-ai/forge-plugin
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,409 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 $0.00000 $0.01409
Opus 5 $0.00000 $0.00705
Sonnet 5 $0.00000 $0.00282
Haiku 4.5 $0.00000 $0.00141

Measured 2d ago against content hash 67f3345ba57a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature 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 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.

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.

docs/commands/feature.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/forge:feature

Design, plan, and implement a new feature end-to-end with structured specs, parallel agent teams, and quality gates.

Level L1 Vibe Coder
Category Feature Development
Syntax /forge:feature [feature name or description]

The Pipeline

graph LR
    A["/forge:feature 'add auth'"] --> B["Phase A: Planner"]
    B -->|approved spec| C["Phase B: Builder"]
    B -->|approved spec| D["Phase B: Testing"]
    C & D -->|code + tests| E["Phase C: Guardian"]
    E -->|all gates pass| F[Done]
    style C fill:#4a9,color:#fff
    style D fill:#4a9,color:#fff

What It Does

/forge:feature is the full-lifecycle feature builder. It takes a feature idea from description through codebase analysis, spec generation, implementation, testing, and validation -- all in one command. The intelligence behind it is a three-phase agent pipeline: Phase A locks interface contracts via the planner agent, Phase B spawns builder and testing agents in parallel to write code and tests simultaneously, and Phase C runs a guardian agent quality gate to catch type errors, test failures, and security issues before you commit.

Before writing a single line, the command analyzes your existing codebase: directory structure, existing patterns, test conventions, and available dependencies. This means the generated spec accounts for how your project actually works, not how a generic project might work. The spec is saved to .claude/plans/ so you can review, modify, or revisit it later.

Without this command, planning a feature means mentally mapping the codebase, writing a spec document by hand, implementing sequentially (code first, tests after), and hoping you catch integration issues. /forge:feature parallelizes the build-and-test phase, enforces quality gates, and records the implementation as knowledge in the orchestrator for future reference.

Syntax & Options

/forge:feature [feature name or description]

Read the full file on GitHub · 129 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 · 129 lines · 0 tokens per session scan A 67f3345ba57a

Subscribe to this mod's changes

feature is a command published in the GitHub repository nxtg-ai/forge-plugin (5 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,409 tokens. 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.