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 opendatahub-io/ai-helpers --skill gist-uploadgit clone --depth 1 https://github.com/opendatahub-io/ai-helpersWrote 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/opendatahub-io/ai-helpers/gist-upload)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/gist-upload"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/gist-upload/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/opendatahub-io/ai-helpers/gist-upload"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/gist-upload.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 17 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00471 |
| Opus 5 | $0.00015 | $0.00235 |
| Sonnet 5 | $0.00006 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
gist-upload 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 12d 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.
What it actually says
Upload to GitHub Gist
Upload content from the current conversation (a plan, summary, analysis, or other output) as a GitHub Gist using the gh CLI.
Prerequisites
ghCLI must be installed and authenticated (gh auth statusshould succeed)
Usage
This skill triggers when the user asks to upload conversation content to a gist, for example:
- "Upload the plan to gist"
- "Upload the summary of our conversation as a gist"
- "Create a gist with the analysis above"
- "Share this as a gist"
Implementation
Step 1: Identify the Content
- Look at the conversation history to identify what the user wants uploaded
- If the user says "the plan", "the summary", "the analysis", etc., find that specific content in the conversation
- If ambiguous, ask the user: "Which part of our conversation should I upload? For example, the plan, summary, or a specific section?"
Step 2: Format the Content
- Take the identified content and format it as clean markdown
- Choose a descriptive filename based on the content type, e.g.
plan.md,summary.md,analysis.md - If the content relates to a specific project or topic, include that in the filename, e.g.
migration-plan.md
Step 3: Upload via gh gist create
- Write the content to a temporary file in
/tmp/ - Upload using
gh:gh gist create /tmp/<filename>- Gists are created as secret by default. Note: secret gists are unlisted, not private, anyone with the URL can view them. Warn the user about this before uploading sensitive content.
- If the user explicitly asks for a public gist, add
--public
- Capture the gist URL from the command output
Step 4: Report and Clean Up
- Show the user the gist URL
- Delete the temporary file
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.
- 12d ago First seen · 52 lines · 29 tokens per session scan A a0b399015b59
gist-upload is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 4d ago), licensed Apache-2.0. It adds 29 tokens to every session and 471 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.
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