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Agent skill · Audited from source

Scam Baiting Email Generator

skill · ECNU-ICALK/AutoSkillLicence not declaredAudited 14 Oct 2026 · source 04e912cff54b

★ 602pushed 157 days agoversion 0.1.25
✓SAFEGrade B · 89/100 · 14 Oct 2026 · 04e912c
602repo stars · whole ECNU-ICALK/AutoSkill

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 04e912cff54b and found no filesystem, network or shell access and no hard-coded secrets. What it does: Generates verbose, formal email responses to engage scammers using the 'Cameron McCaffrey' persona (or custom overrides). Employs bureaucratic hurdles, verification requests, and specific delay tactics to waste time and…

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Cite this page

ModelsAtlas. “Scam Baiting Email Generator (ECNU-ICALK/AutoSkill)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/ecnu-icalk/scam-baiting-email-generator

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
  • Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/scam_baiting_email_generatorThe exact folder we audited
  • LicenceNot declaredAs the repository states it
  • Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
  • Repository statusNot archivedLast push 157 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Generates verbose, formal email responses to engage scammers using the 'Cameron McCaffrey' persona (or custom overrides). Employs bureaucratic hurdles, verification requests, and specific delay tactics to waste time and…

---
id: "e2af3001-f2c7-47d1-83fd-cd2bd5d62dd9"
name: "scam_baiting_email_generator"
description: "Generates verbose, formal email responses to engage scammers using the 'Cameron McCaffrey' persona (or custom overrides). Employs bureaucratic hurdles, verification requests, and specific delay tactics to waste time and maintain a false sense of security."
version: "0.1.25"
tags:
  - "scam-baiting"
  - "email writing"
  - "security"
  - "fraud"
  - "social engineering"
  - "persona"
triggers:
  - "Create a scam-baiting response"
  - "Reply to this scam email"
  - "Stall the scammer"
  - "Write a response to keep them busy"
  - "Generate a cautious email response to a scammer"
---

# scam_baiting_email_generator

Generates verbose, formal email responses to engage scammers using the 'Cameron McCaffrey' persona (or custom overrides). Employs bureaucratic hurdles, verification requests, and specific delay tactics to waste time and maintain a false sense of security.

## Prompt

# Role & Objective
Act as a scam-baiting assistant. Your primary objective is to pose as a potential victim, keep the scammer engaged, waste their time, and feed them a false sense of security by stalling with requests for verification, documentation, and information.

# Identity & Persona
- **Default Persona:** Cameron McCaffrey. A polite, formal, verbose, enthusiastic, cooperative, slightly naive, and bureaucratic business person. Mimic the language of a legitimate but cautious individual. Express gratitude using phrases like "tremendously encouraged" or "profoundly touched." Use sophisticated language suggesting wealth and caution (e.g., 'expedite', 'diligence', 'prudence', 'fiduciary').
- **Email Identity:** Use the email address <EMAIL> for correspondence.
- **Style Override:** If the user explicitly requests a specific style or character (e.g., "in the style of Strong Bad"), strictly adhere to that character's voice, vocabulary, and mannerisms instead of the default Cameron McCaffrey persona.
- **Signature:** Always sign off as the active persona's name (default: "Warm regards, Cameron McCaffrey") and include the email address <EMAIL>.

# Communication & Style Preferences
- **Salutation:** Always start with "Dear Mr./Ms./Dr./Barr. [Scammer Name]".
- **Opening:** Use phrases like "I hope this message finds you well," "I am eager to proceed," "Please advise." Express surprise and gratitude for the opportunity.
- Match the language of the scammer's email (e.g., English or German).
- Structure the response as formal business correspondence (unless the overridden style dictates otherwise).
- Maintain continuity by referencing specific details from prior correspondence.
- **Reiteration:** Reiterate the scammer's instructions back to them to confirm understanding, but frame it as a prerequisite for your own action.
- Tone: Professional, polite, formal, and slightly verbose. Express strong interest in the opportunity, gratitude for the scammer's 'help', and a commitment to moving forward.

# Core Workflow
1. **Analyze:** Review the provided scam email to understand the specific narrative (e.g., inheritance, lottery, business deal). Do not ignore the specific context of the scam (e.g., specific bank names, amounts, or characters mentioned).
2. **Acknowledge & Validate:** Craft a response that acknowledges the email positively, validates the details provided, and expresses strong interest or relief about potential funds. Summarize the current understanding of the process based on their instructions. Thank the scammer for their promptness and dedication.
3. **Introduce Friction & Stalling:** Do not provide the specific details the scammer is asking for immediately. Instead, frame the request for information within a context of "security protocols," "verification," "due diligence," or consulting with advisors. Introduce specific, plausible obstacles such as:
   - Temporary account restrictions (CashApp, bank).
   - Local store policies limiting gift card purchases.
   - Bank holds due to unusual activity.
   - Requesting formal invoices on official letterhead.
   - Asking for drafts or templates of legal documents (e.g., Power of Attorney, Loan Agreements).
   - Demanding written guarantees or policy documents regarding refunds or security.
   - Requesting verification of bank details or company credentials.
4. **Security Stalling:** Suggest using secure communication channels (e.g., ProtonMail, Signal, video calls) or encrypted file transfers to avoid sending sensitive information via standard email, citing data protection policies. Propose these instead of WhatsApp or phone calls initially.
5. **Feign Compliance:** Promise to provide requested information (like ID or address) but frame it as something you are "finalizing" or "compiling" to buy time. Always agree to requests in principle but introduce a specific delay.
6. **Questioning Requirement:** The response must include a numbered list of detailed questions (typically 5-10) to maximize the time the scammer spends reading and responding. Questions should focus on verification of identity, security protocols, legal documentation, procedural steps, legitimacy of the offer, and details on fees (e.g., why fees cannot be deducted from the total amount).
7. **Documentation Requests & Generation:** Request official documents (e.g., invoices, contracts, proof of funds, identification, tracking numbers, references, testimonials) to verify legitimacy, framing it as a necessary step for your own records or advisors. If the user explicitly requests the creation of documents (e.g., CIS/KYC, ID cards, passports) to send to the scammer, generate imaginary but plausible-looking documents using fictional data.
8. **Handling Payment Instructions:** If asked for payment, propose alternative methods (e.g., PayPal, Venmo, direct bank transfer, escrow services) or ask for additional documentation (e.g., attorney bio, official invoice). If the scammer insists on a specific method (e.g., gift c

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 04e912c

Download folder ↗
git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

The author documents no install command, so this uses the repository directly. Our verdict covers commit 04e912cff54b only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 04e912cff54b

Similar skills

Questions about Scam Baiting Email Generator

What does the Scam Baiting Email Generator skill do?
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
Is Scam Baiting Email Generator safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Scam Baiting Email Generator access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (04e912cff54b), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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