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-crisis-response-auditorgit 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-crisis-response-auditor)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/call-crisis-response-auditor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-crisis-response-auditor/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-crisis-response-auditor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/call-crisis-response-auditor.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 | $0.00092 | $0.01516 |
| Opus 5.5 | $0.00037 | $0.00606 |
| Sonnet 5.5 | $0.00018 | $0.00303 |
| Haiku 4.5 | $0.00009 | $0.00152 |
Grade A, and why
call-crisis-response-auditor 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 6d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
call-crisis-response-auditor
A business call can surface a live crisis. An agent that keeps chasing the table while the person is in danger has failed the call, no matter how well the booking went.
Most QA measures task completion. Almost none measure whether the agent stopped and helped when the callee signaled danger. This skill reads a finished call transcript, detects crisis cues in the callee's own turns, and grades the agent's conduct after that moment: did it keep selling, did it stay silent, or did it hand the person to real help?
Why This Skill Exists
A reservation-confirmation call is routine until the callee says "my chest hurts and I can't breathe". At that instant the business task is worth nothing and the correct behavior is narrow and trainable: stop the task, acknowledge, point to 911 / 988 / local emergency, end the call. This auditor turns that behavior into a grade a reviewer can act on, and turns it into a pre-call protocol the goal crafter embeds in every goal.
When To Use
- after any business CALL-E call whose transcript might contain a crisis moment, as a QA gate alongside task-completion checks
- when reviewing a call run whose post_summary sounds off or truncated
- before placing calls to vulnerable populations, to craft a crisis-safe goal template with an embedded crisis protocol
- in CI over fixture corpora, to catch goal templates that would chase business asks through a crisis
Modes
Analyze a finished call
python3 scripts/crisis_response_auditor.py analyze \
--call-result path/to/call-result.json
Accepts the real get_call_run result shape
({status, result: {transcript}}), a bare {transcript: [...]} dict, or
a flat turn list. Emits the report described under Input/Output.
Craft a crisis-safe goal
python3 scripts/crisis_response_auditor.py craft --number +14155550161 \
--business-name "Harbor Grill" --task "confirm the Friday reservation"
--number must be a reserved test number matching
+1[0-9]{3}55501[0-9]{2}. Optional: --language (default en-US).
Emits a goal_template for plan_call whose protocol field instructs
the agent to stop the business task, acknowledge warmly, refer to 911 /
the 988 Suicide and Crisis Lifeline (or local emergency), and end the
call - never diagnose, never counsel, never continue the business ask.
What ships with it
10 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.
- data/example-goal.json 791 B
- data/fixtures/demo-crisis-001.json 445 B
- data/fixtures/demo-crisis-002.json 402 B
- data/fixtures/demo-crisis-003.json 260 B
- data/fixtures/demo-crisis-004.json 267 B
- references/examples.md 5.6 KB
- references/research-papers.md 2.7 KB
- references/safety.md 1.3 KB
- scripts/crisis_response_auditor.py 13 KB runs code
- tests/test_crisis_response_auditor.py 12 KB runs code
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.
- 6d ago First seen · 148 lines · 92 tokens per session scan A c0143f750320
call-crisis-response-auditor is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (109 stars, last pushed yesterday), licensed MIT. It adds 92 tokens to every session and 1,516 once invoked, about $0.0004 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 2026-10-14.
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