arn-code-feature-spec

arn-code-feature-spec is a skill for Claude Code from AppsVortex/arness. It costs 161 tokens per session (8,176 once invoked), scanned A, original, MIT.

A conversational feature-design workflow that turns an idea into a written specification. A specification records what the feature should do, how it fits the system, and the decisions made during planning.

In plain words
What is it for?
Use it to explore a feature idea, break it into parts, assess its architecture, and create a specification for the planning stage.
Why use it?
It helps clarify requirements and technical choices before implementation begins, reducing uncertainty during later planning and coding.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the arn-code plugin — 37 skills, 18 agents shipped together

Good fit Use it to explore a feature idea, break it into parts, assess its architecture, and create a specification for the planning stage.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add AppsVortex/arness
Claude Code
/plugin install arn-code

Made for: Claude Code.

Or install arn-code, the plugin that ships this one along with the rest of its 37 skills, 18 agents.

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 arn-code-feature-spec

README.md
[![agentmods](https://agentmods.dev/badge/skills/appsvortex/arness/arn-code-feature-spec/github.svg)](https://agentmods.dev/skills/appsvortex/arness/arn-code-feature-spec)
Your own site
<a href="https://agentmods.dev/skills/appsvortex/arness/arn-code-feature-spec"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-code-feature-spec/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 arn-code-feature-spec

Your own site · 80×15
<a href="https://agentmods.dev/skills/appsvortex/arness/arn-code-feature-spec"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-code-feature-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 161 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,176 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 $0.00161 $0.08176
Opus 5.5 $0.00064 $0.03270
Sonnet 5.5 $0.00032 $0.01635
Haiku 4.5 $0.00016 $0.00818

Measured 1mo ago against content hash e94a40e55a5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

arn-code-feature-spec 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 1mo 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/arn-code/skills/arn-code-feature-spec/SKILL.md · 500 lines

How it starts

The opening of the file, as written. The whole thing — 500 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Arness Feature Spec

Develop a feature idea into a well-formed specification through iterative conversation, aided by architectural analysis from the arn-code-architect agent and, when the feature involves UI, user experience design from the arn-code-ux-specialist agent. This is a conversational skill that runs in normal conversation (NOT plan mode). The primary artifact is a feature specification written to the project's specs directory that captures requirements, architectural assessment, and decisions from the exploration conversation. The spec then informs plan creation via the /arn-code-plan skill.

Step 0: Ensure Configuration

Read ${CLAUDE_PLUGIN_ROOT}/skills/arn-code-ensure-config/references/step-0-fast-path.md and follow its instructions. This guarantees a user profile exists and ## Arness is configured with Arness Code fields before proceeding.

Workflow

Step 1: Capture the Feature Idea

1a. Detect Backlog Feature (Greenfield Path)

Before asking the user to describe their feature, check if the trigger includes a greenfield feature backlog entry:

  1. Check if the trigger message contains an F-NNN pattern (regex: F-\d{3}). Accept natural invocations like:

    • feature spec F-002
    • spec F-002: Device Pairing
    • feature spec: Device Pairing (fuzzy match against feature file names in the features directory)
  2. Check if conversation context from arn-code-pick-issue includes feature file content (look for markers: ## Description, ## Journey Steps, ## Acceptance Criteria that indicate an F-NNN file was passed inline).

  3. If either condition is met: extract the feature ID and proceed to Step 1b.

  4. If neither condition is met: fall through to the standard flow below (ask the user to describe the feature).

1b. Load Greenfield Feature Context

Only runs when a backlog entry is detected in Step 1a. Loads the feature file, referenced UC documents, and scope boundary context (related features from the Feature Tracker) to provide rich context for the spec exploration. If any greenfield artifact is missing, falls back gracefully.

Read the full file on GitHub · 500 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago First seen · 500 lines · 161 tokens per session scan A e94a40e55a5b

Subscribe to this mod's changes

arn-code-feature-spec is a skill published in the GitHub repository AppsVortex/arness (33 stars, last pushed 2mo ago), licensed MIT. It adds 161 tokens to every session and 8,176 once invoked, about $0.0006 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 2026-08-30.

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