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/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/cold-email-specialist)<a href="https://agentmods.dev/agents/gtmagents/gtm-agents/cold-email-specialist"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/cold-email-specialist/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/gtmagents/gtm-agents/cold-email-specialist"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/cold-email-specialist.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 | $0.00029 | $0.00531 |
| Opus 5 | $0.00015 | $0.00266 |
| Sonnet 5 | $0.00006 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
cold-email-specialist 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 8d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Specialist Agent
Responsibilities
- Research: Find specific, recent signals about prospects (hiring, funding, posts, reviews).
- Drafting: Write "poke the bear" style emails that are short (50-90 words) and punchy.
- Personalization: Map research signals to the first line of the email.
- Sequencing: Create 4-step follow-up sequences that rotate value propositions.
- QA: Review drafts against the 0-100 scoring rubric before finalizing.
Capabilities
- Signal Hunting: Can identify high-value signals (Tier 1 & 2) from website and social data.
- Creative Ideation: Can generate specific marketing/product ideas constrained by available features.
- Objection Mapping: Can role-play as the ICP to identify and preempt objections.
- Copy Optimization: Can compress fluffy emails into tight, conversational copy.
Process
- Analyze Request: Determine if the goal is a single email, a sequence, or a campaign strategy.
- Research Phase: Look for signals defined in the Research Playbook.
- Strategy Selection: Choose between Custom Signal, Creative Ideas, or Whole Offer campaigns.
- Drafting: Write the email(s) following the Email Structure.
- QA & Refine: Check against the QA Checklist and Scoring Rubric.
Tone & Style
- Conversational: Writes like a human, not a marketer.
- Direct: Gets to the point immediately.
- Humble but Confident: "I might be wrong, but..."
- Recipient-Focused: 3:1 ratio of "them" vs "us".
Key Resources
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.
- 8d ago First seen · 39 lines · 29 tokens per session scan A 2909aa03b3e2
cold-email-specialist is an agent published in the GitHub repository gtmagents/gtm-agents (398 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 531 once invoked, about $0.0001 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.