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-planning)<a href="https://agentmods.dev/skills/appsvortex/arness/arn-planning"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-planning/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-planning"><img src="https://agentmods.dev/badge/skills/appsvortex/arness/arn-planning.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 | $0.00167 | $0.06010 |
| Opus 5.5 | $0.00067 | $0.02404 |
| Sonnet 5.5 | $0.00033 | $0.01202 |
| Haiku 4.5 | $0.00017 | $0.00601 |
Grade A, and why
arn-planning 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 — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arness Planning
Go from an idea, issue, or bug report through to a complete implementation plan ready for execution. This is the primary first-citizen entry point for the Arness development pipeline. It orchestrates scope assessment, spec authoring, plan generation, plan structuring, plan review, and task creation — then chains to arn-implementing.
This skill is a sequencer and decision-gate handler. It MUST NOT duplicate sub-skill logic. All pipeline work is done by the invoked skills. Arness-planning handles: input routing, scope assessment, transitions between skills, progress display, resumability, and chaining.
Prerequisites: 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.
After configuration is ensured, extract the following from ## Arness:
- Plans directory — for detecting plan previews and project folders
- Specs directory — for detecting specification files
- Code patterns — path to stored pattern documentation
- Issue tracker — determines if "Pick from backlog" option is available (
github,jira, ornone)
Workflow
Step 0: Input Routing
Check the trigger message to determine the entry path:
| Input Pattern | Action |
|---|---|
| No args | Proceed to Step 1 (State Detection), then G1 if no resume |
| Text description (e.g., "planning: add rate limiting") | Extract description, proceed to Step 3 (Scope Assessment) |
Issue reference (#42, PROJ-123) |
Invoke Skill: arn-code:arn-code-pick-issue with the reference, then proceed to Step 3 with the loaded issue context |
Feature backlog reference (F-003) |
Invoke Skill: arn-code:arn-code-pick-issue with the reference, then proceed to Step 3 |
| "pick" keyword | Invoke Skill: arn-code:arn-code-pick-issue (browse mode), then proceed to Step 3 |
| "resume" | Proceed to Step 1 (State Detection) |
What ships with it
3 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 · 492 lines · 167 tokens per session scan A 90de03d8b54f
arn-planning is a skill published in the GitHub repository AppsVortex/arness (33 stars, last pushed 2mo ago), licensed MIT. It adds 167 tokens to every session and 6,010 once invoked, about $0.0007 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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