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 jscraik/Agent-Skills --skill skill-installergit clone --depth 1 https://github.com/jscraik/Agent-SkillsWrote 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/jscraik/agent-skills/skill-installer)<a href="https://agentmods.dev/skills/jscraik/agent-skills/skill-installer"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/skill-installer/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/jscraik/agent-skills/skill-installer"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/skill-installer.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 | $0.00029 | $0.01521 |
| Opus 5.5 | $0.00012 | $0.00608 |
| Sonnet 5.5 | $0.00006 | $0.00304 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
skill-installer 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Installer
Install the smallest requested skill set, prove where it landed, and keep source, destination, and runtime visibility separate. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimental and can be installed the same way.
Philosophy
Treat installation as a provenance and visibility workflow, not a file copy. List before installing when the user has not named a skill, install only the named package, and report validation as pass, fail, or blocked with the exact source and destination.
Adapt the route to the source: curated names, experimental names, public GitHub paths, and private repo paths need different commands and blocker language. Keep the install surface narrow even when the user mentions several catalogs.
When To Use
- The user asks what curated or experimental skills are available.
- The user names a curated skill to install.
- The user provides a GitHub repo, tree URL, or repo path for a skill package.
- The user asks whether an installed skill is already present locally.
Use the helper scripts based on the task:
- List skills when the user asks what is available, or if the user uses this skill without specifying what to do. Default listing is
.curated, but you can pass--path skills/.experimentalwhen they ask about experimental skills. - Install from the curated list when the user provides a skill name.
- Install from another repo when the user provides a GitHub repo/path (including private repos).
Install skills with the helper scripts.
Communication
When listing skills, output approximately as follows, depending on the context of the user's request. If they ask about experimental skills, list from .experimental instead of .curated and label the source accordingly:
"""
Skills from {repo}:
- skill-1
- skill-2 (already installed)
- ... Which ones would you like installed? """
What ships with it
15 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.
- agents/openai.yaml 221 B
- assets/skill-installer-small.svg 923 B
- assets/skill-installer.png 1.1 KB
- LICENSE.txt 11 KB
- references/contract.yaml 750 B
- references/evals.yaml 3.1 KB
- references/skill-factory/contract.yaml 750 B
- references/skill-factory/evals.yaml 3.1 KB
- references/skill-factory/install-flows.md 12 KB
- references/skill-factory/task-profile.json 1.4 KB
- references/skill-factory/troubleshooting.md 1.4 KB
- references/task-profile.json 1.3 KB
- scripts/github_utils.py 659 B runs code
- scripts/install-skill-from-github.py 9.9 KB runs code
- scripts/list-skills.py 2.9 KB runs code
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 Changed · +77 lines · -24 tokens per session 7e2b1ed0ea10
- 1mo ago First seen · 60 lines · 53 tokens per session scan A ecee18d4fcc1
skill-installer is a skill published in the GitHub repository jscraik/Agent-Skills (9 stars, last pushed 4d ago), licensed Apache-2.0. It adds 29 tokens to every session and 1,521 once invoked, about $0.0001 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 2026-09-03.
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