Borrowing it
Nothing to install: this file belongs to Cloudgeni-ai/opengeni. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Cloudgeni-ai/opengeni/main/.agents/skills/opengeni-presentations/SKILL.mdgit clone --depth 1 https://github.com/Cloudgeni-ai/opengeniWrote 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/cloudgeni-ai/opengeni/opengeni-presentations)<a href="https://agentmods.dev/skills/cloudgeni-ai/opengeni/opengeni-presentations"><img src="https://agentmods.dev/badge/skills/cloudgeni-ai/opengeni/opengeni-presentations/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/cloudgeni-ai/opengeni/opengeni-presentations"><img src="https://agentmods.dev/badge/skills/cloudgeni-ai/opengeni/opengeni-presentations.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.00870 |
| Opus 5 | $0.00029 | $0.00435 |
| Sonnet 5 | $0.00012 | $0.00174 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
opengeni-presentations 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 today.
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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenGeni presentations
The durable OpenGeni artifact is the default working deck. It is the same live object the user sees in the Artifacts dock and slide editor. Never maintain a mutable PPTX shadow or publish a sandbox deck over user edits.
Read references/api.md before editing.
When using skill_read, request that relative path from this Skill; reading
does not materialize a local folder. Use an existing local copy only when the
Skill was installed or explicitly checked out to the filesystem.
Choose the canonical object
- If the user means “this deck” or a visible presentation, call
opengeni__editable_artifact_list, thenopengeni__editable_artifact_getwhen needed. Do not guess from chat text. - To begin empty, call
opengeni__editable_artifact_createwith modalitypresentation. - To begin from a ready workspace PPTX, call
opengeni__editable_artifact_importwith itsfileId. The source remains immutable provenance; the returned artifact becomes the working deck. - Use a standalone local PPTX only when the user explicitly asks to manipulate
sandbox-local bytes and the pinned local runtime is actually available.
Normal import/export uses workspace
fileIdboundaries without local bytes.
Edit and verify
- Inspect metadata and the slide catalog. Before changing a slide, inspect its complete bounded editor scene, including inherited layout facts and notes.
- Plan the narrative and visual system before creating many nodes. Preserve an imported master/layout hierarchy; do not flatten the deck.
- Make the smallest coherent edit. One
opengeni__editable_artifact_applycall is one atomic command batch. Use inspected ids for existing objects andopenGeni.artifacts.ids.stable()for every new master, layout, slide, or node. A direct call must pass the inspectedheadSequenceandstateHash; CodeMode carries its last read head automatically. - For one simple edit, call the artifact tools directly. For loops, generated
ids, slide construction, or several inspections, write auditable Bun code
using
openGeni.artifactsfrom@opengeni/codemode. Both paths execute the exact same frozen tools and authorization. - Inspect every affected slide after mutation. Reconcile bounds, paint order, text, chart/table data, notes, and inheritance. If concurrent work invalidates an assumption, re-inspect and recompute; never force a stale rewrite.
- Export only when the user needs PPTX/PDF/image delivery or visual QA.
opengeni__editable_artifact_export_statusreturns a durable workspacefileId; it does not write into the sandbox. Download only when local bytes are actually needed.
What ships with it
2 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.
- today Changed · +3 lines 9ca173932ab3
- 10d ago First seen · 70 lines · 58 tokens per session scan A 50c912dfe287
opengeni-presentations is a skill published in the GitHub repository Cloudgeni-ai/opengeni (126 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 870 once invoked, about $0.0003 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.
Other skills, from other repositories
press-clip
Turn a live article URL into a press clip that looks like the real coverage — the publication's own logo, fonts, photos and layout kept intact, the ads and clutter removed, and (for a roundup) just the client's section. Renders to PDF. You inspect each site and tailor the removal; the bundled script carries no…
output-dev-eval-testing
Create offline evaluation tests for Output SDK workflows using @outputai/evals. Use when implementing test evaluators with verify(), creating dataset YAML files, building eval workflows, or running workflow tests via CLI.
output-build-workflow
Implement an Output SDK workflow from a plan document. Use when the user asks to build, implement, or code a workflow from an existing plan, or after output-plan-workflow has produced a plan and the user is ready to build.
output-dev-scenario-file
Create test scenario JSON files for Output SDK workflows. Use when creating test inputs, documenting expected behaviors, or setting up workflow testing.
output-plan-workflow
Use when the user asks to create, build, generate, scaffold, or plan a new workflow. Orchestrates the full planning process including architecture, steps, prompts, evaluators, and testing strategy using specialized subagents.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.