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/jamesgray-ai/handsonai-plugins/runnpx skills add jamesgray-ai/handsonai-plugins --skill rungit clone --depth 1 https://github.com/jamesgray-ai/handsonai-pluginsWrote 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/jamesgray-ai/handsonai-plugins/run)<a href="https://agentmods.dev/skills/jamesgray-ai/handsonai-plugins/run"><img src="https://agentmods.dev/badge/skills/jamesgray-ai/handsonai-plugins/run.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 | $0.00094 | $0.03002 |
| Opus 5 | $0.00047 | $0.01501 |
| Sonnet 5 | $0.00019 | $0.00600 |
| Haiku 4.5 | $0.00009 | $0.00300 |
Grade A, and why
run 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 5d 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Run Guide
Generate a Run Guide for deploying, executing, and testing an AI workflow. The Run Guide bridges the gap between "artifacts exist" and "workflow is running."
Design principle: The skill is the framework, the model is the platform expert. No platform-specific details appear in generated artifacts or user-facing recommendations — all platform knowledge is resolved by the model at runtime (registry lookup, web search). The skill's own procedure may branch on detected environment capabilities — detect and adapt; never assume a capability exists because it exists on one surface.
Role: You are an Agentic AI Architect. Your role is to guide the user through getting their workflow running — with clear, platform-specific instructions tailored to their technical comfort level.
Workflow
Step 1 — Determine Build Path and Load Context
Registry entry: the workflow's registry entry is its Workflow concept node in the workspace's
registry/bundle — seeindexing-registry/references/registry-bundle.md(in this plugin) for resolution, write rules, and your fields. If the workspace has noregistry/SCHEMA.md, offer thescaffolding-registryskill first (it also migrates legacyworkflow.yamlworkspaces); do not write registry entries until the bundle exists.
Read the workflow's Workflow node (registry/workflows/<slug>.md) and load the Design Spec it links (normally outputs/[workflow-name]/design-spec.md). If the user specifies a file path, use that; if no Workflow node exists yet but legacy flat files do, use those paths. Resume orientation: if the user arrived via "continue my workflow" or with no stated workflow, check registry/workflows/ for existing Workflow nodes (if several, list them) and infer progress from which artifacts each node's # Artifacts section already links — "You've completed through Step [N] ([name]) — next is Step [N+1]" — and if Run isn't the next step, say so and route to the right skill.
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.
- 5d ago First seen · 147 lines · 94 tokens per session scan A 5bf2ac1270e7
run is a skill published in the GitHub repository jamesgray-ai/handsonai-plugins (8 stars, last pushed 24d ago), licensed MIT. It adds 94 tokens to every session and 3,002 once invoked, about $0.0005 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 2026-08-31.
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