Gini Agent is a personal AI-agent runtime that manages conversations, runs, tasks, approvals, memory, skills, jobs, tools, traces, audit events, and runtime health across its clients. It is for an agent that can remember, learn from task outcomes, and operate through desktop or mobile interfaces with user controls. Catalogue add-ons extend the runtime with skills and instructions.
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/open-curiosity/gini-agent/attachmentsnpx skills add Open-Curiosity/gini-agent --skill attachmentsgit clone --depth 1 https://github.com/Open-Curiosity/gini-agentWrote 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/open-curiosity/gini-agent/attachments)<a href="https://agentmods.dev/skills/open-curiosity/gini-agent/attachments"><img src="https://agentmods.dev/badge/skills/open-curiosity/gini-agent/attachments.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 | $0.00047 | $0.02556 |
| Opus 5 | $0.00023 | $0.01278 |
| Sonnet 5 | $0.00009 | $0.00511 |
| Haiku 4.5 | $0.00005 | $0.00256 |
Grade A, and why
attachments 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attachments
You move bytes between three places:
- Gini upload space —
<id>references for files the user attached in chat, downloaded from a URL, or promoted from workspace. - External URLs — any https endpoint (signed PUT/GET URLs from APIs, raw file URLs, etc.).
- Workspace files — files on disk under the agent's workspace root.
This skill ships four scripts you invoke via skill_run, plus a recipe for each common direction. The base primitive vision_query (asking the model to describe an image upload) is in core, not here — combine it with the scripts below when the model needs to "see" what it just moved.
When to use this skill
- The user attached an image and asks you to file a Linear / GitHub / Notion issue with it.
- The user pasted a URL pointing to file content (Linear attachment, GitHub raw, generic https URL) and asks you to ingest or describe it.
code_exec/terminal_execproduced a workspace file (chart, exported PDF, downloaded artifact) and you need to send it somewhere or runvision_queryon it.- An MCP server returned an
assetUrl/ signed URL pointing to file content and you want to do something with the bytes.
The four scripts
signed-upload — chat-attached upload → external URL
PUT bytes from a Gini upload (chat attachment, downloaded file, promoted workspace file) to a signed URL the model obtained from an API's prepare step. Used in 3-step attachment flows: prepare via the API → signed-upload → finalize via the API.
skill_run({
skill: "attachments",
script: "signed-upload",
args: {
uploadId: "abc-123-...", // from the user message marker, signed-download, or promote-file
url: "https://uploads.linear.app/...?X-Goog-...",
headers: { // pass through whatever the prepare step returned, verbatim
"content-type": "image/png",
"x-goog-content-length-range": "36116,36116"
}
}
})
// → { ok: true, status: 200, bytesSent: 36116 }
// or { ok: false, status, error: "..." }
What ships with it
6 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.
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 · 162 lines · 47 tokens per session scan A 1d697712a6e1
attachments is a skill published in the GitHub repository Open-Curiosity/gini-agent (1,869 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 2,556 once invoked, about $0.0002 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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