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 signal-inspection-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/signal-inspection-listening)<a href="https://agentmods.dev/skills/sonicfieldlabs/akouo/signal-inspection-listening"><img src="https://agentmods.dev/badge/skills/sonicfieldlabs/akouo/signal-inspection-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/signal-inspection-listening"><img src="https://agentmods.dev/badge/skills/sonicfieldlabs/akouo/signal-inspection-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 | $0.00138 | $0.02022 |
| Opus 5 | $0.00069 | $0.01011 |
| Sonnet 5 | $0.00028 | $0.00404 |
| Haiku 4.5 | $0.00014 | $0.00202 |
Grade A, and why
signal-inspection-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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
signal-inspection-listening
Purpose
signal-inspection-listening is the technical and visual ear of akoúō. It listens through file properties, waveform, spectrogram, dynamics, frequency, stereo field, noise, artifacts, transients, and measurable signal behavior.
This mode establishes what can be technically observed before interpretation begins. It also asks what the measurement interface, codec, model, meter, or visualization makes legible and what it cannot prove.
When To Use
Use this skill for:
- file inspection
- audio metadata
- waveform or spectrogram reading
- mastering and production notes
- clipping, distortion, saturation, or limiting
- frequency distribution and spectral profile
- silence, noise floor, hiss, hum, or electrical artifacts
- dynamics, peak level, RMS, LUFS, or dynamic range
- stereo phase, stereo width, or channel imbalance
- audio repair and quality diagnosis
- microsonic events, grains, bursts, pulses, or discontinuities
- forensic caution when technical evidence is needed
Core Question
What can be technically observed, measured, or instrumentally rendered before interpretation begins?
Conceptual Refinements
- Treat waveform, spectrogram, metadata, and model features as technical representations, not direct sonic truth.
- Keep
measuredfor verified inspection only; perceptual description belongs inheard, and production/source guesses belong ininferred. - Separate compression as data reduction from dynamic range compression; name which meaning is intended.
- For machine-listening, ASR, classifier, embedding, or neural-codec outputs, describe the system's representation rather than claiming the system hears.
- A sonic effect may involve signal, space, listener, and context; do not reduce spatial or cultural effects to waveform traits alone.
Input Assumptions
This skill works best with:
- audio files
- file metadata
- waveform data
- spectrogram data
- signal analysis output
- machine-listening or classifier output
- codec, platform, or model metadata
- technical descriptions of audio
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 · 147 lines · 138 tokens per session scan A a5ea7faf4650
signal-inspection-listening is a skill published in the GitHub repository sonicfieldlabs/akouo (10 stars, last pushed 1mo ago), licensed MIT. It adds 138 tokens to every session and 2,022 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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