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/mountainunicorn/add/awaynpx skills add MountainUnicorn/add --skill awaygit clone --depth 1 https://github.com/MountainUnicorn/addWrote 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/mountainunicorn/add/away)<a href="https://agentmods.dev/skills/mountainunicorn/add/away"><img src="https://agentmods.dev/badge/skills/mountainunicorn/add/away.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.01119 |
| Opus 5 | $0.00009 | $0.00560 |
| Sonnet 5 | $0.00003 | $0.00224 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
away 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 3d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADD Away Command v{{VERSION}}
The human is stepping away. Establish what work can proceed autonomously and what must wait.
Phase 1: Understand the Absence
Parse the duration from $ARGUMENTS. If not provided, default to 2 hours. Do not ask — just acknowledge the default:
"No duration specified — I'll plan for a 2-hour session. Say /add:away 4 hours next time to adjust."
Phase 2: Assess Available Work
- Read
.add/config.jsonfor autonomy level and environment tier - Re-read
docs/prd.mdto ground yourself in the project's objectives and scope — this keeps autonomous work aligned with the product vision - Scan
specs/for specs with status "Approved" or "Implementing" - Scan
docs/plans/for plans with status "Approved" or "In Progress" - Check current git status for in-progress work
- Run TodoWrite to see current task list
Categorize Work
Autonomous (can do without human):
- Tasks with clear specs and plans where requirements are unambiguous
- Writing tests for specced features (RED phase)
- Implementing against existing failing tests (GREEN phase)
- Refactoring with test coverage (REFACTOR phase)
- Running quality gates and fixing lint/type errors
- Writing documentation for completed features
- Code review of existing PRs
Queued (needs human decision):
- Any task where the spec is ambiguous or missing
- Architecture decisions with multiple valid approaches
- Deployment to staging or production
- New feature specs (need interview)
- Dependency upgrades with breaking changes
- Anything that would benefit from a Decision Point
Phase 3: Present the Plan
Got it — you'll be away for approximately {DURATION}.
AUTONOMOUS WORK PLAN:
━━━━━━━━━━━━━━━━━━━
{numbered list of tasks, with spec references}
Estimated completion: {rough estimate}
QUEUED FOR YOUR RETURN:
━━━━━━━━━━━━━━━━━━━━━
{numbered list of decisions/tasks that need human input}
I'll maintain a work log and have a return briefing ready.
Phase 4: Get Confirmation
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.
- 3d ago First seen · 121 lines · 17 tokens per session scan A f539aff08522
away is a skill published in the GitHub repository MountainUnicorn/add (11 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 1,119 once invoked, about $0.0001 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.
Other skills, from other repositories
swarm
Launching multi-agent parallel work with the Agentic SDLC. Use when a task benefits from decomposition into parallel subtasks.
finish
Completing a development branch for merge readiness. Use when implementation and tests pass and the branch needs formal preparation for review and merge.
grill
Interrogating requirements to validate before building. Use before swarm decomposition, design decisions on ambiguous features, or when scope creep risk is high.
team
Referencing the agent roster, roles, coordination model, and dispatch modes. Use when spawning agents or checking permissions.
ticket
Associate every PDS task with a GitHub issue. Orchestrator finds or creates the ticket, posts plan and acceptance criteria as a checkbox list, updates it as work progresses. Use at Phase 1 of every swarm.
triage
Triage insights into actionable GitHub issues across repos. Use after running /insights to convert analysis into tracked work.