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 cmj-hub/claude-cold-email --skill cold-email-weekly-rhythmgit clone --depth 1 https://github.com/cmj-hub/claude-cold-emailWrote 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/cmj-hub/claude-cold-email/cold-email-weekly-rhythm)<a href="https://agentmods.dev/skills/cmj-hub/claude-cold-email/cold-email-weekly-rhythm"><img src="https://agentmods.dev/badge/skills/cmj-hub/claude-cold-email/cold-email-weekly-rhythm/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/cmj-hub/claude-cold-email/cold-email-weekly-rhythm"><img src="https://agentmods.dev/badge/skills/cmj-hub/claude-cold-email/cold-email-weekly-rhythm.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 | $0.00092 | $0.01509 |
| Opus 5 | $0.00046 | $0.00754 |
| Sonnet 5 | $0.00018 | $0.00302 |
| Haiku 4.5 | $0.00009 | $0.00151 |
Grade A, and why
cold-email-weekly-rhythm 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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Weekly Rhythm — operational cadence
The framework + the infrastructure are necessary but not sufficient. What separates programs that ship from programs that don't is the weekly cadence. This sub-skill walks the operator through that cadence and surfaces the queue for this week.
Activation
Loaded by cold-email-kickoff when the operator is in iteration mode
(reply data available, brand-config set up).
User-invocable on demand:
- "What's my cold-email rhythm this week"
- "Run the weekly rhythm"
- "Monday queue"
- "Friday review"
The default rhythm (Mon / Wed / Fri)
Monday — PSP signals + list refresh
Goals:
- Refresh the list with this week's signals (≤14 days old)
- Score list quality (dedup, role-fit, freshness)
- Set the week's send target (volume × personalization depth)
Tasks the skill runs:
- Pull signals: For each anchor in
brand-config.psp.signal_anchors, surface 5-10 new candidates from the operator's sources (LinkedIn job search, Crunchbase, RSS, etc.) - Score the list: Invoke
cold-email-list-qualityfor dedup + role-fit + freshness scoring - Set the queue: Recommend send volume based on:
- Warm-up state (
brand-config.infrastructure.warm_up_status) - Reply-rate trend from last week
- Available personalization time
- Warm-up state (
Output:
# Monday — <date>
## This week's send queue
- Volume: <N> sends across <M> sequences
- Personalization depth: deep (≤30/seq) / medium (≤80/seq) / light (≤200/seq)
## Signal hunt (top 5 to verify by Wednesday)
1. <Company> — <signal>
2. <Company> — <signal>
3. ...
## List quality
- Score: <0-100>
- Dedup: <N> removed
- Role-fit: <N> outside ICP — flagged for removal
- Freshness: <N> stale signals removed
## Next: Wednesday ship + Friday review
Wednesday — sequence ship + reply triage
Goals:
- Ship this week's sequence (T1 for new prospects, T2/T3/T4 for in-flight)
- Triage reply pile from earlier in the week
Tasks:
- Draft sequences via
cold-email-craftusing the operator's brand-config + SOUL.md voice - Self-check each draft via
cold-email-revieweragent - Spam-lint via
cold-email-spam-lint - Route to send infrastructure (the operator's actual sending stack)
- Triage replies received since Monday:
- Score each via
cold-email-reply-scoring - Route per
brand-config.operations.reply_routing
- Score each via
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 Changed · -1 lines 6ed4daf72d64
- 11d ago First seen · 186 lines · 92 tokens per session scan A 051a217d7642
cold-email-weekly-rhythm is a skill published in the GitHub repository cmj-hub/claude-cold-email (2 stars, last pushed 2d ago), licensed MIT. It adds 92 tokens to every session and 1,509 once invoked, about $0.0005 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.
Other skills, from other repositories
afrexai-lead-hunter
Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.
graphify
Knowledge graph engine for B2B sales intelligence. Builds queryable graphs from product catalogs, customer conversations, and market research. Powered by graphify.
telegram-toolkit
Register these commands with @BotFather using /setcommands.
lead-discovery
AI-driven lead discovery for B2B export. Searches web for potential buyers matching ICP, evaluates fit, and creates CRM records for follow-up.
b2b-sdr-agent
Open-source B2B AI SDR template. 7-layer context system with 10-stage sales pipeline, 4-layer anti-amnesia memory, 14 automated pipeline checks, WhatsApp IP isolation, multi-channel (WhatsApp+Telegram+Email). Built on OpenClaw.
sdr-humanizer
Transform AI-generated sales messages into natural, human-like conversations that build trust and rapport.