newsletter-campaign-report

newsletter-campaign-report is a skill for Claude Code from Misar-AI/misarblog-mcp. It costs 33 tokens per session (262 once invoked), scanned A, original, MIT.

A workflow for drafting newsletter issues and checking subscriber results on Misar.Blog. A newsletter is an email sent to subscribers, often containing links to new articles.

In plain words
What is it for?
Use it to select published articles, write email introductions and links, review subscribers, and compare newsletter traffic or revenue over time.
Why use it?
It keeps issues consistent with earlier emails and reports only performance data that is actually available.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the misarblog plugin — 7 skills, 3 agents, 2 MCP servers shipped together

Good fit Use it to select published articles, write email introductions and links, review subscribers, and compare newsletter traffic or revenue over time.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/misar-ai/misarblog-mcp/newsletter-campaign-report
Install

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.

Any agent
npx skills add Misar-AI/misarblog-mcp --skill newsletter-campaign-report
Clone the repo
git clone --depth 1 https://github.com/Misar-AI/misarblog-mcp

Made for: Claude Code.

Or install misarblog, the plugin that ships this one along with the rest of its 7 skills, 3 agents, 2 MCP servers.

Wrote 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.

agentmods badge for newsletter-campaign-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/misar-ai/misarblog-mcp/newsletter-campaign-report/github.svg)](https://agentmods.dev/skills/misar-ai/misarblog-mcp/newsletter-campaign-report)
Your own site
<a href="https://agentmods.dev/skills/misar-ai/misarblog-mcp/newsletter-campaign-report"><img src="https://agentmods.dev/badge/skills/misar-ai/misarblog-mcp/newsletter-campaign-report/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.

agentmods 80×15 button for newsletter-campaign-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/misar-ai/misarblog-mcp/newsletter-campaign-report"><img src="https://agentmods.dev/badge/skills/misar-ai/misarblog-mcp/newsletter-campaign-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 262 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.00262
Opus 5 $0.00016 $0.00131
Sonnet 5 $0.00007 $0.00052
Haiku 4.5 $0.00003 $0.00026

Measured 12d ago against content hash b4a0e8c2c649, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

newsletter-campaign-report 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.

skills/newsletter-campaign-report/SKILL.md · 35 lines

What it actually says

Newsletter issues and performance

Drafting an issue

  1. list_my_articles (status=published) for the articles to feature.
  2. list_newsletter_issues to match the structure and voice of past issues — subscribers notice a format that suddenly changes.

For each featured article write a two-sentence hook that earns the click, using its real URL from the API. Open with a short personal intro; close with one call to action, not several.

If fewer articles are available than requested, say so rather than padding the issue with filler.

Reviewing performance

  • list_newsletter_issues — what has been sent
  • list_newsletter_subscribers — audience size and growth
  • get_analytics_summary — revenue and traffic context

Compare issues against each other rather than against generic benchmarks: a newsletter's own baseline is the only meaningful reference for whether an issue landed.

Do not

Fabricate open or click figures for an issue. Report only what the API returns, and name what is missing.

Changes

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.

  1. 12d ago First seen · 35 lines · 33 tokens per session scan A b4a0e8c2c649

Subscribe to this mod's changes

newsletter-campaign-report is a skill published in the GitHub repository Misar-AI/misarblog-mcp (1 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 262 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 2026-08-31.

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