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.
/plugin marketplace add AppsVortex/arness/plugin install arn-codeWrote 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.
[](https://agentmods.dev/skills/appsvortex/arness/arn-code-feature-spec)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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:
-
Check if the trigger message contains an F-NNN pattern (regex:
F-\d{3}). Accept natural invocations like:feature spec F-002spec F-002: Device Pairingfeature spec: Device Pairing(fuzzy match against feature file names in the features directory)
-
Check if conversation context from
arn-code-pick-issueincludes feature file content (look for markers:## Description,## Journey Steps,## Acceptance Criteriathat indicate an F-NNN file was passed inline). -
If either condition is met: extract the feature ID and proceed to Step 1b.
-
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.
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.
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.
- 1mo ago First seen · 500 lines · 161 tokens per session scan A e94a40e55a5b
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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