Brand Voice
affaan-m/ECC
Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows.
Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested.
Apache-2.0Auto-check passed
Install Speaker Recognizer
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/speaker-recognizer .claude/skills/speaker-recognizer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .claude/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/speaker-recognizer .agents/skills/speaker-recognizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .agents/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/speaker-recognizer .cursor/skills/speaker-recognizer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .cursor/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/autonomous-ai/Physical-AI-Operating-System.git --path skills/speaker-recognizer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/speaker-recognizer .gemini/skills/speaker-recognizer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .gemini/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/speaker-recognizer .github/skills/speaker-recognizer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .github/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System speaker-recognizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/speaker-recognizer .opencode/skills/speaker-recognizer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "speaker-recognizer" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/speaker-recognizer into .opencode/skills/speaker-recognizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "speaker-recognizer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
speaker-recognizer- GitHub stars
- 381
- Token cost
- ~1.1k tokens
- SKILL.md length
- 499 words
- Files
- 4
- Skills in repo
- 28
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested.
- SKILL.md covers Entry gate, Decision matrix — after the…, Quick enroll (mic) and Hard rules
- Calls curl and ffmpeg
What it does
Speaker Recognizer is an agent skill from autonomous-ai/Physical-AI-Operating-System. Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested. Unknown Speaker labels, saved audio, and same-tag history alone do not activate this skill. Handle ordinary requests without identity lookup or a name question.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `reference/api.md`, `reference/enroll-flows.md` and `skill.json`).
The repository describes itself as: The open-source operating system for physical AI. The licence is Apache-2.0.
Example prompts
- “/speaker-recognizer”
What it can do on your machine
Read from SKILL.md and the folder at commit f1b9ebe. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
curlffmpeg
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Speaker Recognizer loads about 1.1k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 499 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from autonomous-ai/Physical-AI-Operating-System at commit f1b9ebe, republished under its Apache-2.0 licence (© autonomous-ai). 499 words, ~1,070 tokens.
Download SKILL.mdSave it as
.claude/skills/speaker-recognizer/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- speaker-recognizer
- description
- Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested. Unknown Speaker labels, saved audio, and same-tag history alone do not activate this skill. Handle ordinary requests without identity lookup or a name question.
Speaker Recognizer
Each mic transcript is prefixed Speaker - Name: when recognized, or Unknown Speaker: [voice:voice_N] ... (audio save[d] at <path>...) otherwise. The audio path is the WAV of whoever spoke this turn — use it (with paths from prior same-tag turns when needed) to enroll on POST /speaker/enroll.
Self-enrollment only — never enroll one person's voice under another person's name.
Entry gate
Unknown identity is metadata, not an enrollment request. Without a clear self-introduction, an explicit voice enrollment/management request, or a reply continuing a user-initiated enrollment, handle the actual request directly: no speaker API calls, no enrollment reference reads, no name question, and no replacement acknowledgment. Meaningless fragments follow the device's normal silence rules. Same-tag history alone does not start or resume enrollment; a new unrelated request takes priority.
A name counts only when the speaker identifies themselves, not when addressing the agent ("Mike, open Chrome"), mentioning another person, or appearing in metadata. Preserve any substantive request accompanying a self-introduction; enrollment must not replace it.
Decision matrix — after the entry gate
| Signals in current turn | Prior same-tag turns? | Action |
|---|---|---|
Unknown Speaker: + path + name + ≥25 words | — | Enroll now with current path only. |
Unknown Speaker: + path + name + <25 words | ≥1 prior path same [voice:N] | Enroll now with all same-tag paths (oldest→newest). |
Unknown Speaker: + path + name + <25 words | none | Ask one follow-up: "say your name + ~25–30 words". |
| Explicit enrollment request + path + NO name | any | Ask for the speaker's own name; request more audio only if needed. |
| Reply continuing enrollment, still no name or insufficient audio | same enrollment | Explain what is missing once; do not loop or enroll under a guessed name. |
Speaker - <Name>: | — | Already identified — skill not needed. |
| "who do you know?" / "list voices" | — | GET /speaker/list. |
| "forget my voice" / "remove Alex" | — | POST /speaker/remove. |
| Telegram voice note + intro | — | Convert to WAV + enroll with Telegram fields. |
| Telegram voice note + "who is this?" | — | POST /speaker/recognize. |
When in doubt → see reference/enroll-flows.md. All curl + error handling → reference/api.md.
Show full SKILL.md (183 more words)Show less
Quick enroll (mic)
curl -s -X POST http://127.0.0.1:5001/speaker/enroll \
-H "Content-Type: application/json" \
-d '{"name": "darren", "wav_paths": ["<path1>", "<path2>"]}'Confirm AFTER the API returns ok: "Nice to meet you, <Name>!".
Hard rules
- Self-enrollment only — "this is my friend Bob" → refuse politely; Bob must speak himself.
- Lowercase normalized name — same
nameasface-enrollfor the same person (/root/local/users/<name>/is shared). - Minimum voice for one-turn enroll: ~25 words (aim 25–30) OR combine with prior same-tag turns to ~5–10s total.
- Cluster claim is automatic — pass any path inside
voice_<N>/and the server pulls every sibling WAV. One path is enough. - Two-turn path mapping —
<pathA>= turn BEFORE follow-up,<pathB>= turn AFTER. Never swap. - Telegram audio must be 16 kHz mono WAV before enroll — convert with
ffmpeg -ar 16000 -ac 1; same folder as source. Skip if already.wav. /speaker/identity(not re-enroll) when only linking Telegram info to an existing mic profile.- No unsolicited identity questions — ask only within user-initiated enrollment; combine missing-name and missing-audio guidance in one question. Do not repeatedly interrupt other requests to finish enrollment.
- Confirm every enroll AFTER the API returns ok.
- Don't narrate technical details — no "base64", "ffmpeg", "POST /speaker/enroll".
- Never write files directly — always use the HTTP API.
© autonomous-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files in skills/speaker-recognizer of autonomous-ai/Physical-AI-Operating-System.
- SKILL.md
- reference/api.md
- reference/enroll-flows.md
- skill.json
Open the folder on GitHubat commit f1b9ebe
Compare with similar skills
Speaker Recognizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Speaker Recognizer this skillautonomous-ai/Physical-AI-Operating-System | 381 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Brand Voiceaffaan-m/ECC | 275k | 3 repos | ~912 | Automated safety check: Pass | MIT | |
| Brand Voiceaffaan-m/ECC | 275k | — | ~424 | Automated safety check: Pass | MIT | |
| Brand Voiceaffaan-m/ECC | 275k | — | ~359 | Automated safety check: Pass | MIT | |
| Draft In Voicegarrytan/gbrain | 31k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Email Draft In Voiceyc-software/qm | 15k | — | ~481 | Automated safety check: Pass | MIT |
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从真实的帖子、文章、发布说明、文档或网站文案中构建基于源材料的写作风格档案，然后在内容、外展和社交工作流中重复使用该档案。当用户希望保持声音一致性而不使用通用的AI写作套路时使用。
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Questions about Speaker Recognizer
What does Speaker Recognizer do?
Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested. Speaker Recognizer is an agent skill from autonomous-ai/Physical-AI-Operating-System. Self-enroll voices after a clear self-introduction or explicit enrollment request; continue that enrollment, or list, forget, link, and identify voices when requested.
How do I install Speaker Recognizer in Claude Code?
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a claude-code`. Or copy the skill folder (skills/speaker-recognizer in autonomous-ai/Physical-AI-Operating-System) into .claude/skills/speaker-recognizer in your project. Claude Code loads it when a task matches its description.
How do I install Speaker Recognizer in Codex?
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a codex`. Or copy the skill folder (skills/speaker-recognizer in autonomous-ai/Physical-AI-Operating-System) into .agents/skills/speaker-recognizer in your project. Codex loads it when a task matches its description.
Can I use Speaker Recognizer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill speaker-recognizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/speaker-recognizer, .gemini/skills/speaker-recognizer, .github/skills/speaker-recognizer and .opencode/skills/speaker-recognizer in your project.
What does Speaker Recognizer need to run?
Going by SKILL.md and its folder, Speaker Recognizer needs the command-line tools its instructions call (curl and ffmpeg).
Does Speaker Recognizer access the network?
SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Speaker Recognizer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Speaker Recognizer use?
Speaker Recognizer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Speaker Recognizer use?
About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Speaker Recognizer?
Skills that share tags, products or a category with Speaker Recognizer: Brand Voice (affaan-m/ECC, 275k stars), Brand Voice (affaan-m/ECC, 275k stars), Brand Voice (affaan-m/ECC, 275k stars) and Draft In Voice (garrytan/gbrain, 31k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Speaker Recognizer?
autonomous-ai (a GitHub organization) maintains it in autonomous-ai/Physical-AI-Operating-System, which has 381 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 8, 2026.
Source: autonomous-ai/Physical-AI-Operating-System on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.