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-disfluency-stress-profilergit 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-disfluency-stress-profiler)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-disfluency-stress-profiler"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-disfluency-stress-profiler/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-disfluency-stress-profiler"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-disfluency-stress-profiler.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 | $0.00078 | $0.01397 |
| Opus 5.5 | $0.00031 | $0.00559 |
| Sonnet 5.5 | $0.00016 | $0.00279 |
| Haiku 4.5 | $0.00008 | $0.00140 |
Grade A, and why
call-disfluency-stress-profiler 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 25d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
call-disfluency-stress-profiler
Repeated pauses and repairs can be useful prompts for human review, but do not establish a speaker's emotional state or knowledge.
Spoken conversation carries signals that plain transcripts still preserve:
disfluency. When a callee is stressed, confused, or overwhelmed, their
filled-pause rate (uh, um, er) and self-repair frequency (I mean,
actually, word repetitions) spike measurably above baseline. When an agent
encounters questions outside its prepared knowledge, the same markers appear
in its turns.
This skill reads the finished get_call_run transcript, computes per-side
disfluency rates, and flags CALLEE_STRESSED or AGENT_HESITANT when rates
cross illustrative, unvalidated demo thresholds. It then offers a reassurance-paced follow-up
call goal or a script-review recommendation.
When To Use
- after any CALL-E call where the contact seemed distressed or uncertain
- as part of a QA pipeline to detect agent knowledge gaps at scale
- in healthcare, collections, or support workflows where caller distress carries legal or ethical weight
- to identify topics that consistently cause agent hesitancy (→ update scripts)
When Not To Use
- as a clinical or psychological stress assessment
- during a call; strictly post-call analysis plus pre-call goal crafting
- as the sole basis for medical or legal decisions
- on languages other than English; the lexicon is English-only
Workflow
Audit a finished call
python3 scripts/disfluency_stress_profiler.py analyze \
--transcript path/to/call-result.json
Reads the real get_call_run result shape or the flat fixture shape. Emits
a disfluency card:
agent_profile/callee_profile: per-side stats includingtotal_words,total_markers,disfluency_rate, andper_turn_countsflags[]:CALLEE_STRESSEDand/orAGENT_HESITANTwhen rates exceed their respective thresholdsverdict:NORMAL/CALLEE_STRESSED/AGENT_HESITANT/BOTH_STRESSED, plusunclearpathsrecommended_action: one ofno_action_required,reassurance_followup,review_agent_script, orreassurance_followup_and_script_reviewdisclaimer: heuristic advisory disclaimer on every card
What ships with it
6 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.
- 25d ago First seen · 113 lines · 78 tokens per session scan A 4f607887756c
call-disfluency-stress-profiler is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 1,397 once invoked, about $0.0003 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 2026-09-25.
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