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 CALLE-AI/awesome-phone-call-agents --skill call-acoustic-breath-biomarker-trackergit clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agentsWrote 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/calle-ai/awesome-phone-call-agents/call-acoustic-breath-biomarker-tracker)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-acoustic-breath-biomarker-tracker"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-acoustic-breath-biomarker-tracker/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/calle-ai/awesome-phone-call-agents/call-acoustic-breath-biomarker-tracker"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-acoustic-breath-biomarker-tracker.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 | $0.00042 | $0.00881 |
| Opus 5.5 | $0.00017 | $0.00352 |
| Sonnet 5.5 | $0.00008 | $0.00176 |
| Haiku 4.5 | $0.00004 | $0.00088 |
Grade A, and why
call-acoustic-breath-biomarker-tracker 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 1mo 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Acoustic Breath Biomarker Tracker
This experimental helper calculates a pause ratio from synthetic, pre-segmented durations. It does not capture audio, run VAD, detect a medical condition, assess patient safety, or execute a handoff. Its DYSPNEA_DETECTED, NORMAL, and action enums are illustrative legacy labels, not clinical conclusions. Do not use this prototype for patient triage or emergency decisions.
Scientific Foundation
| Paper / Framework | Source | Relevance |
|---|---|---|
| Detection of Mild Dyspnea from Pairs of Speech Recordings | IEEE ICASSP (2020) | Provides the acoustic feature extraction models for identifying respiratory variations and abnormal pause mechanics. |
| Biomarkers in respiratory diseases | Breathe editorial (2019) | General background, not validation of pause-ratio clinical inference. |
| COVID-19-related voice disorders: a scoping review | PubMed (2026) | Background on voice disorders, not validation of this helper. |
| Software as a Medical Device (SaMD) | FDA (2023) | Regulatory framework for AI algorithms evaluating biological states. |
How it works
- Supply synthetic
AudioSegmentdurations to the helper. - Audio capture and VAD are not included; any future host would provide its own inputs.
- The
process_call_streamfunction evaluates the extracted segments. - A pause ratio at or above the illustrative threshold selects the legacy
DYSPNEA_DETECTEDenum; it does not establish dyspnea. ESCALATE_TO_HUMANis returned as a demo label only. No workflow is halted and no nurse transfer or emergency handoff occurs.
Decision Matrix
| Pause Ratio | Classification | Recommended Action |
|---|---|---|
>= 0.40 |
DYSPNEA_DETECTED |
ESCALATE_TO_HUMAN |
< 0.40 |
NORMAL |
PROCEED_NORMALLY |
Ratio < 0 (no data) |
INSUFFICIENT_DATA |
INDETERMINATE |
Configuration Reference
| Parameter | Default | Range | Description |
|---|---|---|---|
pause_threshold_ratio |
0.40 |
0.30 - 0.60 |
Ratio of pause time over total time to trigger dyspnea flag. |
segment_duration_ms |
500 |
250 - 2000 |
Window size for acoustic feature extraction. |
What ships with it
5 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.
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.
- 1mo ago First seen · 68 lines · 42 tokens per session scan A 10a4e70c703a
call-acoustic-breath-biomarker-tracker is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 881 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-19.
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