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 sentdm/sent-plugin --skill messaging-performance-analyzergit clone --depth 1 https://github.com/sentdm/sent-pluginWrote 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/sentdm/sent-plugin/messaging-performance-analyzer)<a href="https://agentmods.dev/skills/sentdm/sent-plugin/messaging-performance-analyzer"><img src="https://agentmods.dev/badge/skills/sentdm/sent-plugin/messaging-performance-analyzer/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/sentdm/sent-plugin/messaging-performance-analyzer"><img src="https://agentmods.dev/badge/skills/sentdm/sent-plugin/messaging-performance-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 6 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00084 | $0.02794 |
| Opus 5.5 | $0.00034 | $0.01118 |
| Sonnet 5.5 | $0.00017 | $0.00559 |
| Haiku 4.5 | $0.00008 | $0.00279 |
Grade A, and why
messaging-performance-analyzer 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Messaging performance analyzer
Overview
Use this skill to turn raw Sent message evidence into a concise diagnosis of what changed, where the funnel leaks, and what to fix first. Anchor every analysis to Sent message IDs, message status, message activities, and webhook events before interpreting carrier, WhatsApp, or RCS provider codes.
Sent’s v3 send endpoint accepts a template-based request and returns per-recipient message_id values for asynchronous tracking. Status is retrieved with GET /v3/messages/{id}, and detailed lifecycle evidence is retrieved with GET /v3/messages/{id}/activities. Webhook endpoints support event ingestion, event-type discovery, event history, test delivery, and secret rotation.
When to use
Use this skill when the user asks why messages failed, why delivery or read rate dropped, whether fallback is working, whether a provider is filtering traffic, or how a campaign performed. Trigger on words such as “MDR,” “delivery report,” “webhook event,” “activities,” “status,” “failed,” “undelivered,” “read rate,” “fallback,” “filtering,” “throttling,” or “carrier reject.”
Do not use this skill to register 10DLC, design a Sender Profile, onboard RCS, or author WhatsApp templates. Hand those workflows to the related skills after the performance symptom is isolated.
Evidence hierarchy
Start with Sent-owned evidence, then enrich it with provider context. This prevents overfitting to a carrier code that may be missing, stale, or normalized differently across channels.
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.
- 1mo ago First seen · 143 lines · 84 tokens per session scan A c50f9395374a
messaging-performance-analyzer is a skill published in the GitHub repository sentdm/sent-plugin (51 stars, last pushed yesterday), licensed MIT. It adds 84 tokens to every session and 2,794 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 2026-08-30.
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