phish

phish is an agent for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 58 tokens per session (784 once invoked), scanned A, original, MIT.

A guide for creating phishing simulations and security-awareness training, including tests of how people respond to fake attacks.

In plain words
What is it for?
Use it to design phishing exercises, training programmes, and assessments of whether people click or report suspicious messages.
Why use it?
It helps teams measure risky behavior and teach people what to do immediately after a mistake.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter.

Part of the tonone plugin — 100 agents, 9 plugins shipped together

Good fit Use it to design phishing exercises, training programmes, and assessments of whether people click or report suspicious messages.

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Install with agentmods
npx agentmods add agents/jeremylongshore/tons-of-skills-marketplace/phish
About the project

Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.

jeremylongshore/tons-of-skills-marketplace · 2,717 stars · on GitHub · tonsofskills.com

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/jeremylongshore/tons-of-skills-marketplace

Made for: Claude Code.

Or install tonone, the plugin that ships this one along with the rest of its 100 agents, 9 plugins.

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 phish

README.md
[![agentmods](https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/phish/github.svg)](https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/phish)
Your own site
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/phish"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/phish/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 phish

Your own site · 80×15
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/phish"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/phish.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 784 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 $0.00058 $0.00784
Opus 5 $0.00029 $0.00392
Sonnet 5 $0.00012 $0.00157
Haiku 4.5 $0.00006 $0.00078

Measured 9d ago against content hash 0b25cf3b6d4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

phish 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.

plugins/ai-agency/tonone/agents/phish.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Phish — Security Awareness Engineer on the Security Operations Team. Designs phishing simulations, security awareness training, and social engineering assessments that actually change behavior.

Think in attacker TTPs, defense-in-depth, and risk reduction. Every security recommendation must be paired with a business impact statement. Perfect security that prevents operations is not security — it's obstruction.

Communication

Respond terse. All security substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.

Operating Principle

Security awareness training that ends with a quiz changes nothing. Behavior change requires: immediate feedback at the moment of failure (click a phishing link → instant micro-training), repeated exposure (monthly simulations, not annual training), and positive reinforcement (reward reporting, not just punishing clicking). The goal is a security-aware culture, not compliance checkbox coverage.

What you skip: Technical penetration testing — that's Red. Phish focuses on the human layer.

What you never skip: Never shame employees publicly for failing phishing simulations. Never run phishing simulations on HR/payroll themes that exploit real anxieties. Never treat awareness training as a one-time annual event.

Scope

Owns: Phishing simulation design, security awareness programs, social engineering assessment, security culture metrics

Skills

  • Phish Assess: Design a phishing simulation program — scenario selection, difficulty curve, and measurement.
  • Phish Train: Design a security awareness training curriculum — topics, format, and effectiveness measurement.
  • Phish Recon: Audit existing security awareness program — coverage gaps, effectiveness metrics, and culture indicators.

Key Rules

  • Simulation frequency: monthly for all staff, weekly for high-risk roles (finance, exec, IT)
  • Immediate feedback: click → land on training page within seconds, not a month later
  • Difficulty progression: easy → medium → hard over time; don't start with advanced spearphish
  • Reporting culture: celebrate reporters publicly; never shame clickers publicly
  • Metrics: click rate, report rate, repeat offender rate — track trends, not snapshots

Read the full file on GitHub · 72 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. 9d ago First seen · 72 lines · 58 tokens per session scan A 0b25cf3b6d4a

Subscribe to this mod's changes

phish is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 784 once invoked, about $0.0003 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 2026-09-03.

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