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.
npx skills add ognjengt/founder-skills --skill outreach-specialistgit clone --depth 1 https://github.com/ognjengt/founder-skillsWrote 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/skills/ognjengt/founder-skills/outreach-specialist)<a href="https://agentmods.dev/skills/ognjengt/founder-skills/outreach-specialist"><img src="https://agentmods.dev/badge/skills/ognjengt/founder-skills/outreach-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/skills/ognjengt/founder-skills/outreach-specialist"><img src="https://agentmods.dev/badge/skills/ognjengt/founder-skills/outreach-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00042 | $0.03050 |
| Opus 5 | $0.00021 | $0.01525 |
| Sonnet 5 | $0.00008 | $0.00610 |
| Haiku 4.5 | $0.00004 | $0.00305 |
Grade A, and why
outreach-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 12d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outreach Specialist
Purpose
Generate a personalized outreach sequence (default 3 messages) that sounds human, builds trust, and books calls — tailored to the prospect, platform, and offer.
Execution Logic
Check $ARGUMENTS first to determine execution mode:
If $ARGUMENTS is empty or not provided:
Respond with: "outreach-specialist loaded, tell me who you're reaching out to and what you're offering"
Then wait for the user to provide their requirements in the next message.
If $ARGUMENTS contains content:
Proceed immediately to Task Execution (skip the "loaded" message).
Task Execution
When user requirements are available (either from initial $ARGUMENTS or follow-up message):
1. MANDATORY: Read Reference Files FIRST
BLOCKING REQUIREMENT — DO NOT SKIP THIS STEP
Before doing ANYTHING else, you MUST use the Read tool to read ALL reference files. This is non-negotiable:
Read: ./references/outreach-templates.md
Read: ./references/sequence-strategy.md
What you will find:
- outreach-templates.md: 8 proven outreach message templates with examples, psychology, and when-to-use logic
- sequence-strategy.md: Follow-up sequence structures, timing, and platform-specific rules
DO NOT PROCEED to Step 2 until you have read all files and have their content in context.
2. Check for Business Context
Check if FOUNDER_CONTEXT.md exists in the project root.
- If it exists: Read it and extract everything relevant to outreach: company name, offer, ICP, value proposition, case studies, brand voice, pricing model.
- If it doesn't exist: Proceed using defaults from "Defaults & Assumptions."
3. Analyze Input & Determine What's Missing
From the user's requirements, extract:
- Who they're reaching out to (ICP, role, company type)
- What they're offering (product, service, specific solution)
- What platform (LinkedIn DM, email, X DM, Instagram DM, other)
- The goal (book a call, get a reply, send a lead magnet, get a referral)
- Available proof (case studies, results, testimonials, metrics)
- Sequence length (default: 3 messages if not specified)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 311 lines · 42 tokens per session scan A 7e6ed8798aa3
outreach-specialist is a skill published in the GitHub repository ognjengt/founder-skills (302 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 3,050 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…