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 WYRE-AI/msp-claude-plugins --skill messagesgit clone --depth 1 https://github.com/WYRE-AI/msp-claude-pluginsWrote 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/wyre-ai/msp-claude-plugins/messages)<a href="https://agentmods.dev/skills/wyre-ai/msp-claude-plugins/messages"><img src="https://agentmods.dev/badge/skills/wyre-ai/msp-claude-plugins/messages/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/wyre-ai/msp-claude-plugins/messages"><img src="https://agentmods.dev/badge/skills/wyre-ai/msp-claude-plugins/messages.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00037 | $0.02434 |
| Opus 5 | $0.00018 | $0.01217 |
| Sonnet 5 | $0.00007 | $0.00487 |
| Haiku 4.5 | $0.00004 | $0.00243 |
Grade A, and why
Abnormal Security Messages 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 9d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Abnormal Security Message Analysis
Overview
Abnormal Security provides deep message analysis capabilities beyond basic threat detection. This skill covers message retrieval, header inspection, attachment analysis, sender authentication results, and delivery context. Use it when performing forensic analysis of specific emails or investigating delivery patterns.
Anti-triggers
- Where a message went, or why it never arrived — Abnormal sees
messages only as evidence attached to a detected threat. It has no
delivery pipeline, no queue, and no bounce record, so "trace this
email" questions belong to the gateway: use
Mimecast Message Tracking. - Removing the message from inboxes, or putting it back — that is
the remediation surface; use
Abnormal Security Threats. - Inspecting a message a gateway is holding — everything Abnormal
can show was already delivered. Pre-delivery holds are
SpamTitan QuarantineorProofpoint Quarantine.
Message Field Reference
These are response fields describing what Abnormal reports about a
message. They are not tool parameters — the only parameters the message
tools accept are threatId and messageId. Availability varies by
message and by tenant configuration; treat any single field as
best-effort.
Core Message Fields
| Field | Type | Description |
|---|---|---|
abxMessageId |
string | Abnormal's identifier for the message, as returned in the abnormal_messages_list response |
subject |
string | Email subject line |
fromAddress |
string | From header email address |
fromName |
string | From header display name |
toAddresses |
string[] | All To: recipients |
ccAddresses |
string[] | All CC: recipients |
bccAddresses |
string[] | All BCC: recipients (if available) |
sentTime |
datetime | When the email was sent |
receivedTime |
datetime | When the email was received by Abnormal |
internetMessageId |
string | RFC 5322 Message-ID header |
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.
- 9d ago First seen · 261 lines · 37 tokens per session scan A 56467d63fe74
Abnormal Security Messages is a skill published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 7d ago), licensed Apache-2.0. It adds 37 tokens to every session and 2,434 once invoked, about $0.0002 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.
Other skills, from other repositories
live-preview
Mid-build visual verification loop. Takes screenshots of components during construction, not just after. Catches visual regressions and invisible features before they compound. Requires Playwright or similar screenshot tool.
content-card-news
A planning tool for four-card social media carousels on Instagram, Threads, and Kakao Channel, combining card copy, design guidance, image prompts, captions, and hashtags.
cs-voc-triage
A customer-feedback analysis tool that combines reviews and support contacts from multiple channels. VOC means “voice of the customer”: the comments, questions, complaints, and praise customers leave about a business.
design-copywriting
A copywriting workflow for marketing and product pages that uses a brand voice and returns structured text for page sections.
data-realestate
A lookup tool for reported South Korean property transactions using Ministry of Land data. It covers sales and rental deals for apartments, officetels, multi-family homes, houses, and commercial or office properties.
meta-feedback
A feedback reporter that collects bug reports and feature requests, then formats them as GitHub Issues. GitHub Issues are shared records used by development teams to track work and problems.