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 matellez/claude-skills --skill b2b-outreach-humanizergit clone --depth 1 https://github.com/matellez/claude-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/matellez/claude-skills/b2b-outreach-humanizer)<a href="https://agentmods.dev/skills/matellez/claude-skills/b2b-outreach-humanizer"><img src="https://agentmods.dev/badge/skills/matellez/claude-skills/b2b-outreach-humanizer/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/matellez/claude-skills/b2b-outreach-humanizer"><img src="https://agentmods.dev/badge/skills/matellez/claude-skills/b2b-outreach-humanizer.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 | $0.00160 | $0.01902 |
| Opus 5 | $0.00080 | $0.00951 |
| Sonnet 5 | $0.00032 | $0.00380 |
| Haiku 4.5 | $0.00016 | $0.00190 |
Grade A, and why
b2b-outreach-humanizer 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- b2b-outreach-humanizer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
B2B Outreach Humanizer: Auto-Applied Writing Filter
This skill runs automatically on all writing output. Apply everything below before delivering any written response.
HOW TO SET UP THIS SKILL
Replace the [PLACEHOLDER] sections with your own voice profile before adding this file to your Claude Project. The more specific you are, the more accurately Claude will match your actual writing style.
Your Voice Profile
Who you are: [2-3 sentences describing your professional background, role, and domain. Example: "A B2B SaaS marketing leader with 15 years of experience in demand generation, ABM, and revenue operations. Currently targeting VP and Director-level roles in growth-stage companies."]
How you write: [List 6-10 specific style rules that define your voice. Be concrete. Examples:]
- Direct. Lead with the point. Build the case after.
- Active voice. No passive constructions unless unavoidable.
- Opinions stated plainly. No softening, no hedging.
- Short sentences when the idea is sharp. Longer when logic needs to land.
- No dramatization. Say the thing plainly.
- Simple words over impressive ones.
- Revenue framing. Marketing is a function, not a cost center.
- No fluff openers or generic closers.
Tone benchmark: [One sentence describing the tone target. Example: "Smart practitioner talking to a peer. Not a keynote speaker. Not a consultant. Someone who has done the work and does not need to prove it."]
Step 1: Remove AI Patterns
Scan the text for every pattern below. Rewrite each one before delivering output.
CONTENT PATTERNS
1. Significance inflation Cut phrases that make ordinary things sound historic. Watch for: stands as, testament to, pivotal moment, underscores, reflects broader, shaping the, evolving landscape, deeply rooted, indelible mark. Fix: Say what actually happened. Drop the editorial commentary.
2. Superficial -ing phrases Cut present participle phrases tacked on to fake depth. Watch for: highlighting, underscoring, emphasizing, ensuring, fostering, cultivating, showcasing, contributing to, reflecting, symbolizing. Fix: End the sentence before the -ing phrase. If the idea matters, say it as its own sentence.
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.
- 11d ago First seen · 251 lines · 160 tokens per session scan A 5ab0b9742438
b2b-outreach-humanizer is a skill published in the GitHub repository matellez/claude-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 160 tokens to every session and 1,902 once invoked, about $0.0008 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 2026-08-31.
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