post-send-analysis

post-send-analysis is a skill for Claude Code from mailgun/mailgun-plugins. It costs 31 tokens per session (485 once invoked), scanned A, original, Apache-2.0.

A tool for reviewing what happened after an email was sent through Mailgun, an email delivery service. It examines delivery results, failures, complaints, unsubscribes, engagement, and related sending details.

In plain words
What is it for?
Use it to investigate one campaign or send, compare it with another period, inspect suppressions and bounces, and break results down by provider, recipient group, template, or domain.
Why use it?
It helps explain poor campaign results or missing messages by connecting delivery problems to recipients, providers, domains, templates, or time periods. It can distinguish different kinds of delivery failure.

Skill for Claude Code

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

Part of the mailgun-claude plugin — 15 skills, 7 commands, 1 MCP server shipped together

Good fit Use it to investigate one campaign or send, compare it with another period, inspect suppressions and bounces, and break results down by provider, recipient group, template, or domain.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mailgun/mailgun-plugins/post-send-analysis
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 mailgun/mailgun-plugins --skill post-send-analysis
Clone the repo
git clone --depth 1 https://github.com/mailgun/mailgun-plugins

Made for: Claude Code.

Or install mailgun-claude, the plugin that ships this one along with the rest of its 15 skills, 7 commands, 1 MCP server.

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 post-send-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/mailgun/mailgun-plugins/post-send-analysis/github.svg)](https://agentmods.dev/skills/mailgun/mailgun-plugins/post-send-analysis)
Your own site
<a href="https://agentmods.dev/skills/mailgun/mailgun-plugins/post-send-analysis"><img src="https://agentmods.dev/badge/skills/mailgun/mailgun-plugins/post-send-analysis/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 post-send-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/mailgun/mailgun-plugins/post-send-analysis"><img src="https://agentmods.dev/badge/skills/mailgun/mailgun-plugins/post-send-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 485 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 $0.00031 $0.00485
Opus 5.5 $0.00012 $0.00194
Sonnet 5.5 $0.00006 $0.00097
Haiku 4.5 $0.00003 $0.00049

Measured 2mo ago against content hash c40a271ca3e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

post-send-analysis 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 2mo 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.

plugins/mailgun-claude/skills/post-send-analysis/SKILL.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Post Send Analysis

Use this skill when the user asks how a send performed, why a campaign underperformed, what happened after a message was sent, or whether a delivery issue is tied to a domain, recipient group, campaign, tag, template, or provider.

Use deliverability triage for broad ongoing failure diagnosis. Use this skill for a bounded review of one send, campaign, template, tag, or time window.

Intake

Ask for domain, region, date range, message ID or storage key when available, campaign tag, template name/version, recipient segment, and the question the user wants answered.

Workflow

  1. Define the analysis window and compare it to a previous similar window when useful.
  2. Query logs and metrics for delivery, permanent failures, temporary failures, complaints, unsubscribes, opens, clicks, providers, devices, and countries.
  3. Check suppressions when recipients report missing mail or logs show dropped messages.
  4. Use bounce classification when failures need category level explanation.
  5. Segment findings by domain, provider, tag, template, sender identity, recipient group, or subaccount when those dimensions are relevant.
  6. Identify whether the issue appears domain specific, recipient specific, campaign specific, template specific, provider specific, or caused by suppressions.
  7. Return a concise summary, evidence table, likely causes, data gaps, and safe next steps.

Interpretation

  • Missing opens or clicks can be caused by disabled tracking, per message tracking overrides, client privacy behavior, or low engagement.
  • A queued or accepted send can still fail later, so use logs rather than only the original API response.
  • Suppressed recipients may not produce an obvious send failure to the caller.
  • Provider concentrated failures deserve separate diagnosis from account wide failures.
  • Complaint rate, bounce rate, and unsubscribes should be reviewed alongside positive engagement.

Safety

Keep analysis diagnostic unless the user asks for remediation. Do not resend, remove suppressions, modify templates, change tracking, or alter account settings without explicit confirmation.

Read the full file on GitHub · 42 lines

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. 2mo ago First seen · 42 lines · 31 tokens per session scan A c40a271ca3e8

Subscribe to this mod's changes

post-send-analysis is a skill published in the GitHub repository mailgun/mailgun-plugins (2 stars, last pushed 15d ago), licensed Apache-2.0. It adds 31 tokens to every session and 485 once invoked, about $0.0001 per session on Opus 5.5. 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.

Related

Other skills, from other repositories

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…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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…

vercel/next.js · 95 tokens

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.

microsoft/vscode · 53 tokens

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…

microsoft/vscode · 71 tokens

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…

vercel/next.js · 83 tokens