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 agentmods add skills/markmhendrickson/ateles/import-audionpx skills add markmhendrickson/ateles --skill import-audiogit clone --depth 1 https://github.com/markmhendrickson/atelesWrote 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/markmhendrickson/ateles/import-audio)<a href="https://agentmods.dev/skills/markmhendrickson/ateles/import-audio"><img src="https://agentmods.dev/badge/skills/markmhendrickson/ateles/import-audio.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00053 | $0.01265 |
| Opus 5 | $0.00026 | $0.00633 |
| Sonnet 5 | $0.00011 | $0.00253 |
| Haiku 4.5 | $0.00005 | $0.00127 |
Grade A, and why
import-audio 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Import Audio
Import audio files from Desktop and macOS Voice Memos, transcribe with Whisper, and store transcriptions. Follows data entry and migration rules for locations and storage order.
When to Use
Use this skill when:
- User says "import audio", "import audio files", "transcribe audio from desktop", or "import voice memos"
- User wants to batch-import and transcribe audio from Desktop or Voice Memos
Required Documents (load first)
- Audio import workflow: docs/data_entry_requirements_rules.mdc (Audio File Import Workflow)
- Storage order: docs/neotoma_parquet_migration_rules.mdc (Neotoma first, then Parquet if still used)
Workflow
- Scan sources for audio files (
.wav,.mp3,.m4a,.ogg,.flac,.aac,.wma,.mp4,.webm,.qta):~/Desktop~/Library/Group Containers/group.com.apple.VoiceMemos.shared/Recordings/(macOS Voice Memos)
- Import files to
$DATA_DIR/imports/audio/with timestamped names:- Desktop files are moved.
- Voice Memos files are copied (system-managed; do not move).
- Transcribe using OpenAI Whisper via
execution/scripts/transcribe_audio.py, or run the full pipeline withexecution/scripts/import_audio_from_desktop.py. - Store transcriptions: Neotoma MCP first per migration rules; if transcriptions still in Parquet, use
$DATA_DIR/transcriptions/transcriptions.parquetvia Parquet MCP. - Auto-invoke
/analyze-meetingon each successfully transcribed file. The analyze-meeting skill's own "skip silently" rule (≥2 speakers OR ≥200 words AND a commitment verb) handles non-meeting audio (voice memos, lectures, ambient recordings) so unrelated audio does not produce spurious tasks/emails/issues. Disable per-run with--no-analyze. - Link continuations: After all transcriptions are stored, review the batch for recordings that are continuations of each other (same topic, recorded within minutes, or explicitly referencing a previous memo). Create a
continuesrelationship between them in Neotoma (earlier → later). - Extract and relate entities: For each transcription, identify mentioned entities — people, places, organizations, topics, tasks, decisions, feedback items, etc. — and create or update corresponding Neotoma entities. Then relate each transcription to every entity it produced or updated using a
mentionsrelationship (transcription → entity).
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.
- 4d ago First seen · 74 lines · 53 tokens per session scan A ba6078dbb38c
import-audio is a skill published in the GitHub repository markmhendrickson/ateles (6 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 1,265 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 2026-08-31.
Other skills, from other repositories
implement
Автономная реализация задачи через изолированный субагент с чистым контекстом.
qqbot-media
QQ Bot 媒体发送指南。教 AI 如何发送图片给用户。.
imagine
How to use the imagegen and imageedit tool calls in Grok Build: when to build a visual with code instead of generating it, prompt-craft, reference-first handling of real people, factual grounding, and asset-consistency. Load this whenever generating or editing an image is on the table, i.e. when an imagegen or…
video-generation
Guide to video generation in MassGen. Use when creating videos from text prompts or images across Grok, Google Veo, and OpenAI Sora backends.
multimedia-backend-integrator
Reference guide for adding new media generation backends to MassGen's unified generatemedia tool.
audio-generation
Guide to audio generation and understanding in MassGen. Covers text-to-speech, music, sound effects, and audio understanding across ElevenLabs and OpenAI backends.