openai_realtime
Skill897 starsChanged 4 months agoMITArchived repositoryView on GitHub
OpenAI native Realtime audio, images and tools over the host's ordinary selected context.
- Reads credentials
2 other projects use a version of this.
Adopted by
Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data
Most recently taken up by
- razzant/ouroborosword for word, first seen Nov 8, 2026
Other versions2 projects use a version of this.
Word for word · 2
- razzant/ouroboros★ 1.7k100% same
- joi-lab/ouroboros-desktop★ 209100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- docs/llms.txtllms.txt
- Browser speechSkill
- Device voiceSkill
- gemini_liveSkill
- grok_realtimeSkill
- live_conversationSkill
- telegramSkill
- TemplatesSkill
- ui_designSkill
- unix_computer_useSkill
- windows_computer_useSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 24
Call instructions follow host system text.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Registers openai_realtime:openai for gpt-realtime-2.1. The host selects
memory, roles, tools and output allowance. The provider owns wire layout,
acknowledgements, captions, usage axes and its catalog. The route's window is the
measured lower bound: 133,554 input tokens accepted and answered on 2026-10-20
(documented context 128,000); spoken retention is still unmeasured. Automatic
truncation is disabled.
Text fields preserve every character and role across the observed 256000-character
item limit. Images remain native input. Unsupported content fails explicitly.
Call instructions follow host system text. The first language tag supplies the
ISO-639-1 transcription hint; additional tags stay in instructions. Pause maps
to server-VAD silence duration (300/500/1000 ms); interruptions follow the owner's
option. Responses remain host-driven, after setup and context/tool ACKs. Respond
opens the greeting; silent tool outputs request no answer.
The native per-response limit encodes allowances up to 4096 directly; larger
allowances use "inf" (the model maximum). An unknown model maximum stays unknown.
Usage reports text/audio/image/cache input and text/audio output independently,
with raw usage and completion status, including interrupted or failed responses.
Reasoning stays in raw usage and is already included in text output, never charged
again as separate thinking tokens. Video has zero usage; frames are billed as images.
There is no diagnostic probe or per-connection reservation in this package.
Renewal opens a fresh host-refitted session; there is no resumption. Native
transcription, response and tool/ACK work must finish first (renewal_ready);
the feature also waits for playback and durable caption writes. The host owns
history, tools, shared spending and Stop. Credentials are read only while opening
an admitted connection. Granting a key does not enable Calls (beta).
Catalog checked 2026-10-21: thinking follows reasoning.effort (minimal through
xhigh); the ten built-in voices remain available.
This provider declares silent context updates: fitted catch-up history with
respond=False does not open an answer, allowing the host to prepare a successor.
Host-only bookkeeping is absent from the structured wire projection; content strings stay exact. Delivered setup and update rows become exposure evidence only at a usable response, before queued updates are released. Host fitting owns the shared remedies and exact physical-cut checkpoints; the provider does not choose a memory horizon.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

