speaker-recognizer

speaker-recognizer is a skill for Claude Code, Codex from autonomous-ai/autonomous-os. It costs 132 tokens per session (993 once invoked), scanned A, original, Apache-2.0.

A voice-enrollment guide for recognizing people who introduce themselves. It uses recorded microphone or Telegram voice-note audio to associate a person's voice with their stated name.

In plain words
What is it for?
Use it when an unknown speaker says their name, when earlier recordings with the same voice tag can be combined, or when a Telegram voice note contains an introduction.
Why use it?
It prevents voices from being saved under the wrong name and explains when a short introduction needs more audio or a follow-up request. Recognized speakers can then be identified in later transcripts.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when an unknown speaker says their name, when earlier recordings with the same voice tag can be combined, or when a Telegram voice note contains an introduction.

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Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-os/speaker-recognizer
Install

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.

Any agent
npx skills add autonomous-ai/autonomous-os --skill speaker-recognizer
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-os

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for speaker-recognizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/speaker-recognizer.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-os/speaker-recognizer)
Your own site
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/speaker-recognizer"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/speaker-recognizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 993 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00132 $0.00993
Opus 5 $0.00066 $0.00496
Sonnet 5 $0.00026 $0.00199
Haiku 4.5 $0.00013 $0.00099

Measured 7d ago against content hash 533bde91aa6c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

speaker-recognizer scanned grade A with 1 finding 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 7d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

When in doubt → see `reference/enroll-flows.md`. All curl + error handling → `reference/api.md`.
skills/speaker-recognizer/SKILL.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Decision matrix — pick ONE action per turn

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".
Unknown Speaker: + path + NO name + <25 words none Ask one follow-up.
Unknown Speaker: + path + NO name ≥1 prior path same [voice:N] (still no name) Reply with a SHORT ack ("Mm, nghe rồi" / "Got it"). NEVER NO_REPLY. Don't re-ask.
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.

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, !".

Hard rules

  • Self-enrollment only — "this is my friend Bob" → refuse politely; Bob must speak himself.
  • Lowercase normalized name — same name as face-enroll for 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.
  • Don't spam "who are you?" — at most once per cluster, and include the "25–30 words" guidance in the same message.
  • Never go silent on Unknown Speaker fragments — when no name and you've already asked, emit a short ack. NO_REPLY is forbidden.
  • 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.

Read the full file on GitHub · 53 lines

Files

What ships with it

3 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.

Changes

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.

  1. 7d ago First seen · 53 lines · 132 tokens per session scan A 533bde91aa6c

Subscribe to this mod's changes

speaker-recognizer is a skill published in the GitHub repository autonomous-ai/autonomous-os (277 stars, last pushed 2d ago), licensed Apache-2.0. It adds 132 tokens to every session and 993 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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