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 linecanary-monitorgit 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/linecanary-monitor)<a href="https://agentmods.dev/skills/calle-ai/awesome-phone-call-agents/linecanary-monitor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/linecanary-monitor/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/linecanary-monitor"><img src="https://agentmods.dev/badge/skills/calle-ai/awesome-phone-call-agents/linecanary-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 62 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 63 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 64 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 65 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 66 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00076 | $0.01106 |
| Opus 5 | $0.00038 | $0.00553 |
| Sonnet 5 | $0.00015 | $0.00221 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
linecanary-monitor 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LineCanary Monitor
Use this skill when the user cares about a phone line staying healthy: an IVR menu, an AI receptionist, a front-desk line — anything customers dial.
It drives the runnable linecanary app,
which places at most one CALL-E call per check per invocation, validates the
structured result against operator-written assertions, compares timing and
answers against the line's own history, and exits 0/1/2 for automation.
When to use
- "Is our phone line / voice agent still working?" — run the checks live and interpret the report.
- "Watch this line" / "monitor our IVR" — set up config, verification and a host schedule (cron or GitHub Actions; the app never self-schedules).
- "Did the voice-agent deploy break anything?" — run the smoke check
(
--only <check-id>) after a deploy, gate on the exit code. - "Why did the canary page?" — read the JSON report and the baseline history, explain the regression kinds in plain words.
When not to use
- The line belongs to someone else and the user cannot verify ownership or produce a written authorization. LineCanary refuses unverified lines; do not help work around that — it is the product's compliance boundary.
- The user wants outbound calls to customers, leads or arbitrary businesses. That is not monitoring; decline and point at the safety notes.
- Sub-minute check frequency or bulk parallel probing. See
references/safety.md— keep schedules proportionate (15–60 minutes is the intended shape).
How it works
- Config as code:
linecanary.config.jsondeclares lines (with anownershipblock), checks (task + strictresultSchema+ assertions + timing bounds + confidence floor) and alerting. Full semantics inreferences/config-reference.md. - Ownership verification: a
greeting_codeline is verified by one call that must hear the operator's code in the line's own greeting; client lines under written authority useattestation. Verification is pinned to the phone number — a changed number re-verifies. - Every run is dry-run by default and prints the plan without dialing.
--liveplaces the calls, evaluates, diffs against the baseline history and appends to it. Every call opens with an AI disclosure. - Exit codes:
0healthy ·1regressions or failing checks ·2the run itself broke (config, credentials, API). Treat1as "page a human",2as "the monitoring is broken, not the line".
What ships with it
3 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.
- 12d ago First seen · 94 lines · 76 tokens per session scan A 0de04636bbdf
linecanary-monitor is a skill published in the GitHub repository CALLE-AI/awesome-phone-call-agents (88 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 1,106 once invoked, about $0.0004 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 2026-08-30.
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