phishing-simulation-analyst

phishing-simulation-analyst is an agent for Claude Code from WYRE-AI/msp-claude-plugins. It costs 96 tokens per session (1,688 once invoked), scanned A, original, Apache-2.0.

An agent that analyses phishing-simulation campaigns for a client or portfolio, focusing on click-rate trends and repeat clickers. Phishing simulations are controlled tests that imitate phishing messages to measure behaviour safely.

In plain words
What is it for?
Use it to ask whether phishing-test performance is improving, which users click repeatedly, and where remedial training should focus.
Why use it?
It puts individual campaign results into a time-based context and names the people who repeatedly fail tests. That makes follow-up training easier to target.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the awareness-pack plugin — 3 skills, 3 commands, 3 agents shipped together

Good fit Use it to ask whether phishing-test performance is improving, which users click repeatedly, and where remedial training should focus.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst
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.

Clone the repo
git clone --depth 1 https://github.com/WYRE-AI/msp-claude-plugins

Made for: Claude Code.

Or install awareness-pack, the plugin that ships this one along with the rest of its 3 skills, 3 commands, 3 agents.

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 phishing-simulation-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst.svg)](https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/phishing-simulation-analyst)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 96 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,688 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.
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 $0.00096 $0.01688
Opus 5 $0.00048 $0.00844
Sonnet 5 $0.00019 $0.00338
Haiku 4.5 $0.00010 $0.00169

Measured 4d ago against content hash 9a7b13378592, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 4d 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.

msp-claude-plugins/awareness-pack/agents/phishing-simulation-analyst.md · 160 lines

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

Read the full file on GitHub · 160 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. 4d ago First seen · 160 lines · 96 tokens per session scan A 9a7b13378592

Subscribe to this mod's changes

phishing-simulation-analyst is an agent published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 5d ago), licensed Apache-2.0. It adds 96 tokens to every session and 1,688 once invoked, about $0.0005 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 2026-09-04.

Related

Other agents, from other repositories

close-auditor

You are a skeptical, evidence-first auditor of finance deliverables: financial statements, close packages, budget-variance reports, tax calculations, and IR financial models. You operate in a strictly read-only capacity — you inspect artifacts and report findings; you never fix them yourself.

modu-ai/moai-cowork · 85 tokens

review-rails

Rails conventions and architecture reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-rails with artifact paths. Ensures existing framework features are used, not reinvented — reads changed files in full and compares them against siblings and the framework-native form.

hoblin/claude-ruby-marketplace · 64 tokens

review-ticket-delivery

Ticket-delivery reviewer for PR audits. Spawned by /rpi:review-pr as subagenttype rpi:review-ticket-delivery with artifact paths. Code-quality reviewers judge how the work was done; this one judges whether the work was done. Runs on every review; carries the always-on security sweep.

hoblin/claude-ruby-marketplace · 68 tokens

implement-executor

Executes a SINGLE implementation task using strict TDD red-green-refactor. Writes failing tests first, verifies they FAIL, then writes minimum implementation to pass, then refactors. Receives one task, PROJECTCOMMANDS, and TDD protocol from the orchestrator. Returns structured TDD evidence. Use for individual tasks in…

racecraft-lab/racecraft-plugins-public · 74 tokens

security-auditor

Senior Security Auditor. Performs OWASP-aligned vulnerability analysis on source code, classifies findings by severity, and produces a structured audit report. Fills the "Security / Edge-Case Auditor" role in the Graph Planning Phase 1 Fan-Out Trio (see graph-planning-superpowers-policy.md §2.3 and…

richfrem/agent-plugins-skills · 77 tokens

audit-design

Audits plugin design quality — over-engineering, hook quality, and architectural patterns. Dispatched by /hone during Phase 2.

acostanzo/quickstop · 30 tokens