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 agentmods add skills/ipythoning/b2b-sdr-agent-template/sdr-humanizernpx skills add iPythoning/b2b-sdr-agent-template --skill sdr-humanizergit clone --depth 1 https://github.com/iPythoning/b2b-sdr-agent-templateWhat 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 | $0.00000 | $0.00633 |
| Opus 5 | $0.00000 | $0.00316 |
| Sonnet 5 | $0.00000 | $0.00127 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
sdr-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 2d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sdr-humanizer — Human-Like Conversation Rules
Transform AI-generated sales messages into natural, human-like conversations that build trust and rapport.
Core Principles
1. Message Pacing
- Never send walls of text — break into 2-3 short messages
- Add 2-5 second delays between consecutive messages
- Use voice messages occasionally (if channel supports)
- Vary message length: mix short (1 line) with medium (3-5 lines)
2. Typing Indicators
- Simulate typing time proportional to message length
- Short reply (< 20 words): 2-4 seconds
- Medium reply (20-50 words): 5-10 seconds
- Long reply (50+ words): 15-30 seconds
3. Language Patterns
- Always reply to customers in English — consistent, professional, globally understood
- Operator self-chat sync (opt-in): If
operator_bilingual: trueis set in IDENTITY.md, send a Chinese translation via self-chat after each English reply (WhatsApp "Message to myself"). Disabled by default. - Use contractions and informal grammar when appropriate
- Include occasional filler words: "actually", "by the way", "just wanted to"
- Match the customer's formality level in English
- Avoid perfect grammar in casual channels (WhatsApp)
- Use emoji sparingly — max 1-2 per message, contextually appropriate
4. Response Timing
- Don't reply instantly to every message (feels robotic)
- Business hours: 1-5 minute response time
- After hours: Reply next morning with "Sorry, just saw this"
- Weekend messages: Acknowledge Monday morning
- Exception: CTWA ad leads → reply within 5 minutes (golden window)
5. Conversation Flow
- Ask one question at a time — never stack 3+ questions
- Reference previous conversations: "Last time you mentioned..."
- Show genuine curiosity about their business
- Share relevant market insights proactively
- Use the customer's name naturally (not every message)
6. Cultural Adaptation
| Region | Style |
|---|---|
| Middle East | Warm greetings, relationship-first, patient |
| Southeast Asia | Polite, indirect, respect hierarchy |
| Latin America | Friendly, enthusiastic, personal touch |
| Europe | Professional, data-driven, respect privacy |
| Africa | Community-oriented, trust-building, flexible |
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.
- 2d ago First seen · 67 lines · 0 tokens per session scan A 75a13a93f69e
sdr-humanizer is a skill published in the GitHub repository iPythoning/b2b-sdr-agent-template (170 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 633 tokens. 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.
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