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 skills add sonicfieldlabs/akouo --skill transductive-media-listeninggit clone --depth 1 https://github.com/sonicfieldlabs/akouoWrote 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/sonicfieldlabs/akouo/transductive-media-listening)<a href="https://agentmods.dev/skills/sonicfieldlabs/akouo/transductive-media-listening"><img src="https://agentmods.dev/badge/skills/sonicfieldlabs/akouo/transductive-media-listening/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/sonicfieldlabs/akouo/transductive-media-listening"><img src="https://agentmods.dev/badge/skills/sonicfieldlabs/akouo/transductive-media-listening.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00147 | $0.02115 |
| Opus 5 | $0.00073 | $0.01058 |
| Sonnet 5 | $0.00029 | $0.00423 |
| Haiku 4.5 | $0.00015 | $0.00212 |
Grade A, and why
transductive-media-listening 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 12d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
transductive-media-listening
Purpose
transductive-media-listening is the mediation ear of akoúō. It listens to conversion: how something becomes sound through technical, biological, computational, electrical, archival, or symbolic transformation.
This mode asks what is transformed, lost, invented, compressed, amplified, tokenized, or hallucinated when one domain becomes sonic or machine-readable.
When To Use
Use this skill for:
- sonification
- biosensors
- hydrophones
- contact microphones
- field recording devices
- AI-generated audio
- voice cloning
- speech-to-text outputs
- datasets and model training material
- sample packs
- compression artifacts
- degraded media
- installations
- sensor-to-sound systems
- algorithmic or model-mediated audio
- platform-mediated recordings and uploads
Core Question
What is transformed, lost, invented, compressed, amplified, or hallucinated when one domain becomes sonic?
Conceptual Refinements
- Transduction is conversion across energies, bodies, signals, media, institutions, and interpretive regimes; it is never neutral transport.
- Acoustic technics produce phenomena as well as capture them: microphones, hydrophones, codecs, headphones, sonograms, instruments, and platforms each create a distinct listening relation.
- Separate machine listening, voice agents, ASR cascades, speech-native systems, neural audio codecs, and generative audio; they are not interchangeable.
- Sonification and data-to-sound mappings are interfaces and arguments, not transparent evidence of the source data.
- Anthropological or archival transduction can turn listening practices into legible objects; treat this as mediation with historical and political stakes.
Input Assumptions
This skill can work with:
- an audio file
- metadata about capture devices or platforms
- microphone, sensor, codec, or model details
- a sonification mapping description
- an AI audio generation prompt
- a dataset description
- a transcript produced by speech-to-text
- an archive or field recording note
- machine-listening, ASR, classifier, embedding, or codec-token output
What ships with it
7 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.
- references/claim-taxonomy.schema.json 5.3 KB
- references/ensemble.schema.json 1.8 KB
- references/listening-context.schema.json 7.7 KB
- references/listening-output.schema.json 11 KB
- references/listening-pass.schema.json 2.4 KB
- references/listening-provenance.schema.json 3.9 KB
- references/route-decision.schema.json 1.8 KB
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.
- 12d ago First seen · 162 lines · 147 tokens per session scan A 24ae13390f98
transductive-media-listening is a skill published in the GitHub repository sonicfieldlabs/akouo (10 stars, last pushed 1mo ago), licensed MIT. It adds 147 tokens to every session and 2,115 once invoked, about $0.0007 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.
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