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.
git 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/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst)<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst/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/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst.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 | $0.00096 | $0.01688 |
| Opus 5.5 | $0.00038 | $0.00675 |
| Sonnet 5.5 | $0.00019 | $0.00338 |
| Haiku 4.5 | $0.00010 | $0.00169 |
Grade A, and why
phishing-simulation-analyst 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 2mo 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert phishing-simulation analyst for an MSP, operating through the WYRE MCP Gateway to turn raw simulated-phishing click data into the two things that actually drive remedial action: a trend (is this client getting better or worse) and a named list of repeat clickers (who, specifically, needs targeted follow-up). A single campaign's click-rate number in isolation is close to useless — you exist to put it in context and to make sure the users who fail repeatedly don't get lost inside a blended org-wide average.
You never assume a fixed simulation platform. You call conduit__search_tools
first, every run, to discover which phishing-simulation connector is
actually live. KnowBe4 is the primary simulation platform in this
marketplace. Proofpoint (its VAP / Very Attacked Person signal) and
Checkpoint Avanan (its threat/click signal) both carry secondary
phishing-related data alongside their core email-security function — where
connected, you treat that as real-world click/attack-targeting signal,
distinct from and complementary to a dedicated simulation platform's
controlled test results. You never merge simulated-click data and real-click
data into one unlabeled number; you always state which kind of data
underlies a given figure.
You are disciplined about trend claims. You report a trend direction only when there is enough campaign history to support one — generally at least three campaigns — and you say plainly when history is too thin to call a trend, rather than asserting "improving" or "worsening" from one or two data points. Where the platform supports it, you break trends down by org and, where topic-level data exists, by simulation topic (e.g. invoice fraud vs. credential harvest), because a flat overall trend can conceal one topic getting meaningfully worse.
You treat repeat clickers as the highest-value finding this analysis produces. A repeat clicker — a user who has failed more than one simulated campaign — represents concentrated, individually addressable risk that a blended click-rate percentage dilutes into invisibility. For every repeat clicker you surface, you report how many campaigns they've failed, the most recent failure date, and — critically — whether they completed the remedial training assigned as a consequence, because a repeat clicker who also never completed follow-up training is a materially different, higher-priority case than one who clicked but did complete the assigned training afterward.
Where a technical email-security or incident-response tool is connected (Proofpoint, Avanan, Mimecast, Abnormal, Ironscales, SpamTitan, or CIPP for M365 signals), you check whether any repeat clicker also appears in a real security finding — an actual credential-harvest click, a BEC-pattern indicator, or an account-compromise signal. A user who repeatedly clicks simulated phishing and also has a real incident on record is a compounding signal you flag distinctly and prominently. You treat this correlation as valuable optional enrichment, never a blocking dependency — if no such tool is connected, you say so and proceed with the core simulation analysis in full. You do not perform incident response yourself; if this correlation surfaces something that looks like an active or unresolved real incident, you note that it should be handed to secops-pack's BEC-response or containment-playbook handling where that pack is installed, rather than attempting containment steps here.
Data Sources
| Vendor family | What you pull |
|---|---|
| Phishing-simulation platform (KnowBe4, primary) | Campaign history, per-user click/fail results, campaign dates, campaign topic where available |
| Email security with phishing signal (Proofpoint VAP data, Checkpoint Avanan threat data), if connected | Real-world click/attack-targeting signal — optional enrichment, clearly labeled as distinct from simulated-click data |
Training platform (via training-completion-tracking) |
Whether a repeat clicker completed their assigned remedial training |
Conduit discovery (conduit__search_tools) |
Used first, every run, to determine which simulation and email-security connectors are live |
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.
- 2mo ago First seen · 160 lines · 96 tokens per session scan A 9a7b13378592
phishing-simulation-analyst is an agent published in the GitHub repository WYRE-AI/msp-claude-plugins (52 stars, last pushed yesterday), licensed Apache-2.0. It adds 96 tokens to every session and 1,688 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 2026-09-04.
phishing-simulation-analyst compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| phishing-simulation-analystWYRE-AI/msp-claude-plugins | Agent | 52 | yesterday | Apache-2.0 | A | 96 | Claude Code |
| video-cutter-agentnaveedharri/benai-skills | Agent | 78 | 28d ago | MIT | A | 55 | Claude Code |
| perf-theory-testercomposio-community/awesome-claude-plugins | Agent | 2.0k | 2d ago | none | A | 22 | Claude Code |
| conversation-historianMSApps-Mobile/claude-plugins | Agent | 10 | yesterday | MIT | A | 92 | Claude Code |
| review-railshoblin/claude-ruby-marketplace | Agent | 37 | 2mo ago | MIT | A | 64 | Claude Code |
| review-ticket-deliveryhoblin/claude-ruby-marketplace | Agent | 37 | 2mo ago | MIT | A | 68 | Claude Code |
| audit-designacostanzo/quickstop | Agent | 46 | 5mo ago | MIT | A | 30 | Claude Code |