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 skills add ariffazil/arifOS --skill tasksgit clone --depth 1 https://github.com/ariffazil/arifOSWrote 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/ariffazil/arifos/tasks)<a href="https://agentmods.dev/skills/ariffazil/arifos/tasks"><img src="https://agentmods.dev/badge/skills/ariffazil/arifos/tasks/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/ariffazil/arifos/tasks"><img src="https://agentmods.dev/badge/skills/ariffazil/arifos/tasks.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 | $0.00023 | $0.01869 |
| Opus 5.5 | $0.00009 | $0.00748 |
| Sonnet 5.5 | $0.00005 | $0.00374 |
| Haiku 4.5 | $0.00002 | $0.00187 |
Grade A, and why
tasks scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST https://api.linear.app/graphql \ The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 192 lines · 23 tokens per session scan A be080377f10d
tasks is a skill published in the GitHub repository ariffazil/arifOS (54 stars, last pushed today), licensed AGPL-3.0. It adds 23 tokens to every session and 1,869 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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aef-assistant
Expert guide and operational workflows for the Agentic Engineering Framework (AEF). Use when interacting with AEF tasks, governance gates (Tier 0, task focus), inceptions, BVP scoring, component fabric, memory recall, subagents, and TermLink mesh.
CONSTITUTIONAL-REFLEX
CANONICAL VERSION: arifos-act v3.0.0 at /root/AAA/skills/arifos-act/SKILL.md This file is kept for OpenCode system instruction backward compatibility. The constitutional reflex arc: ART (pre-kernel) → Kernel (F1-F13) → ACT (post-kernel execution).
kanban-orchestrator
Decomposition playbook + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.
linear
Linear: manage issues, projects, teams via GraphQL + curl.
kanban-worker
Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBANGUIDANCE (from agent/promptbuilder.py); this skill is what you load when you want deeper detail on specific scenarios.