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.
npx agentmods add skills/appsvortex/arness/arn-code-pick-issuenpx skills add AppsVortex/arness --skill arn-code-pick-issuegit clone --depth 1 https://github.com/AppsVortex/arnessWhat 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 | $0.00180 | $0.04160 |
| Opus 5 | $0.00090 | $0.02080 |
| Sonnet 5 | $0.00036 | $0.00832 |
| Haiku 4.5 | $0.00018 | $0.00416 |
Grade A, and why
arn-code-pick-issue 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.
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arness Pick Issue
Browse issues filtered by Arness labels, select one for assessment, and route it to the appropriate Arness pipeline skill for implementation. When a greenfield feature backlog with a Feature Tracker exists, offers local-first dependency resolution to surface unblocked features without network calls.
Step 1: Check Prerequisites
If no ## Arness section exists in the project's CLAUDE.md, inform the user: "Arness is not configured for this project yet. Run /arn-planning to get started — it will set everything up automatically." Do not proceed without it.
Read the Issue tracker field from ## Arness config in the project's CLAUDE.md (values: github, jira, or none). If the Issue tracker field is not present, fall back to legacy detection: check for GitHub: yes and treat as github; otherwise treat as none.
If Issue tracker is github
git rev-parse --is-inside-work-tree— confirm the working directory is inside a git repository.git remote -v— confirm a GitHub remote exists (the origin URL must containgithub.com).gh auth status— confirm the GitHub CLI is authenticated.
If any check fails, inform the user what is missing and suggest running /arn-planning to get started. Do not proceed until all prerequisites are satisfied.
If Issue tracker is jira
- Read Jira project and Jira site from
## Arnessconfig - Verify the Atlassian MCP server is available (attempt a lightweight MCP call, e.g., list projects)
- If the MCP server is not available: "The Atlassian MCP server is not available. Run
/mcpto check status, or run/arn-planningto reconfigure."
If Issue tracker is none
Check for a greenfield feature backlog before stopping:
- Read
## Arnessconfig — check if a Vision directory field exists (only set byarn-spark-init, never by corearn-code-init) - If Vision directory exists, check if
<vision-dir>/features/feature-backlog.mdexists - If the file exists, check if it contains a
## Feature Trackertable
What ships with it
1 file 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.
- 2d ago First seen · 305 lines · 180 tokens per session scan A 43687d618fec
arn-code-pick-issue is a skill published in the GitHub repository AppsVortex/arness (33 stars, last pushed 1mo ago), licensed MIT. It adds 180 tokens to every session and 4,160 once invoked, about $0.0009 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 2026-08-30.
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