caller-reputation-monitor

caller-reputation-monitor is a skill for Claude Code, Codex from DataSift-Ty-Personal/SiftStack. It costs 131 tokens per session (1,944 once invoked), scanned A, original, MIT.

A monitoring workflow for outbound caller IDs, which are the phone numbers shown to people receiving calls. It uses SmrtPhone call results to track when a number may be getting treated as spam.

In plain words
What is it for?
It is for registering caller IDs, reviewing daily call outcomes, creating an HTML health dashboard, and deciding when numbers need rest or remediation.
Why use it?
It helps identify declining answer rates and manage numbers through warm-up, active, watch, rest, or retirement stages before calling performance worsens.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for registering caller IDs, reviewing daily call outcomes, creating an HTML health dashboard, and deciding when numbers need rest or remediation.

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Install with agentmods
npx agentmods add skills/datasift-ty-personal/siftstack/caller-reputation-monitor
Install

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.

Any agent
npx skills add DataSift-Ty-Personal/SiftStack --skill caller-reputation-monitor
Clone the repo
git clone --depth 1 https://github.com/DataSift-Ty-Personal/SiftStack

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for caller-reputation-monitor

README.md
[![agentmods](https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/caller-reputation-monitor/github.svg)](https://agentmods.dev/skills/datasift-ty-personal/siftstack/caller-reputation-monitor)
Your own site
<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/caller-reputation-monitor"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/caller-reputation-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.

agentmods 80×15 button for caller-reputation-monitor

Your own site · 80×15
<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/caller-reputation-monitor"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/caller-reputation-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,944 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00131 $0.01944
Opus 5 $0.00066 $0.00972
Sonnet 5 $0.00026 $0.00389
Haiku 4.5 $0.00013 $0.00194

Measured 12d ago against content hash 9673f735b4d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

caller-reputation-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.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/dashboard.py, scripts/monitor_run.cmd, scripts/monitor.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/caller-reputation-monitor/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Caller ID Reputation Monitor

Keep the user's outbound dialing numbers (DIDs) out of carrier spam labels: register them (prevention), monitor them daily (detection), rest and remediate the ones that degrade (recovery). Built for SmrtPhone users doing REI cold calling, but the concepts apply to any dialer.

The core insight: carriers never tell you a number is flagged. The truest signal you can get for free is your OWN answer rate cratering on a specific number. This skill reads that straight from the user's SmrtPhone call log. No Telnyx account, no port, no monthly fee for the default setup.

What is in this skill

  • references/quick-start.md - the 15-minute setup guide. START HERE for a new user.
  • references/registration-and-remediation.md - why numbers get flagged, the free registration walkthrough (Free Caller Registry), and the runbook for clearing a number that is flagged right now.
  • references/reputation-workflow.md - the full design: signal layers, fusion rules, the number lifecycle state machine, data model.
  • references/telnyx-api-contract.md - verified Telnyx endpoints and fields (only needed for the optional carrier-grade upgrade).
  • references/methodology.md - the deep research behind the whole system (carrier analytics engines, STIR/SHAKEN, healthy call-behavior targets, sources).
  • scripts/ - the complete working monitor. Stdlib-only Python except the two Playwright helpers.

How the monitor works (know this before helping)

Two signal layers, fused as worst-of:

Layer Source Signal Cost
L1 own traffic (default) SmrtPhone call log (smrtphone_cdr.py) per-number ASR, ALOC, short-call % over a trailing 7-day window free
L2 carrier reputation (optional, OFF by default) Telnyx Number Reputation + Remediation API carrier-grade spam_risk / spam_category + auto-remediation $100/mo + porting numbers to Telnyx

L1 healthy targets (SmrtPhone's own published bands): ASR >= 30%, ALOC >= 30 seconds, short calls (under 6s) <= 15% of outbound. A breach makes a number at least Watch, never Flagged on L1 alone. Below 15 dials in the window the sample is too small and L1 abstains (protects warm-up numbers).

Read the full file on GitHub · 80 lines

Changes

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.

  1. 12d ago First seen · 80 lines · 131 tokens per session scan A 9673f735b4d3

Subscribe to this mod's changes

caller-reputation-monitor is a skill published in the GitHub repository DataSift-Ty-Personal/SiftStack (22 stars, last pushed yesterday), licensed MIT. It adds 131 tokens to every session and 1,944 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 2026-08-30.

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