engagement-inbox-manager

engagement-inbox-manager is a skill for Claude Code from iamwaqargulzar/Marketing-Agent-OS. It costs 216 tokens per session (913 once invoked), scanned A, original, Apache-2.0.

A social-media inbox management guide for comments, direct messages, and mentions. It creates a ranked queue and helps classify the tone or intent behind messages.

In plain words
What is it for?
Use it to triage comments and DMs, draft replies, decide whether fan content can be reposted, and define inbox service levels and escalation paths.
Why use it?
It helps teams handle incoming messages consistently, spot messages needing escalation, and set response-time expectations.

Skill for Claude Code

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

Part of the marketing-agent-os plugin — 173 skills shipped together

Good fit Use it to triage comments and DMs, draft replies, decide whether fan content can be reposted, and define inbox service levels and escalation paths.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager
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 iamwaqargulzar/Marketing-Agent-OS --skill engagement-inbox-manager
Clone the repo
git clone --depth 1 https://github.com/iamwaqargulzar/Marketing-Agent-OS

Made for: Claude Code.

Or install marketing-agent-os, the plugin that ships this one along with the rest of its 173 skills.

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 engagement-inbox-manager

README.md
[![agentmods](https://agentmods.dev/badge/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager/github.svg)](https://agentmods.dev/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager)
Your own site
<a href="https://agentmods.dev/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager"><img src="https://agentmods.dev/badge/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager/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 engagement-inbox-manager

Your own site · 80×15
<a href="https://agentmods.dev/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager"><img src="https://agentmods.dev/badge/skills/iamwaqargulzar/marketing-agent-os/engagement-inbox-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 216 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 913 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 $0.00216 $0.00913
Opus 5 $0.00108 $0.00456
Sonnet 5 $0.00043 $0.00183
Haiku 4.5 $0.00022 $0.00091

Measured 7d ago against content hash 38987151cbe2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

engagement-inbox-manager 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 7d 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/engagement-inbox-manager/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engagement Inbox Manager

Quick Start

Use this skill for engagement inbox manager. Start from the user’s concrete objective and available evidence; do not substitute generic marketing advice for task-specific analysis.

Skill Contract

  • Reads: user-provided context; relevant project files; .agents/product-marketing.md when present; approved public or connected data sources.
  • Writes: recommendations and artifacts in the response by default. Persistent file/account changes require explicit request or authorization.
  • Evidence: label consequential claims as measured, user-provided, calculated, estimated, or proxy. Never upgrade uncertainty silently.
  • Side effects: do not publish, send, spend, delete, mutate accounts, or persist registry truth without user authorization.
  • Freshness: verify current platform rules, search eligibility, ad policies, model/tool capabilities, laws, pricing, and other time-sensitive claims before acting.

Instructions

  1. Define the exact engagement inbox manager objective, audience/scope, constraints and success metric before recommending action.
  2. Load shared product-marketing context when it materially changes the answer; ask only for missing facts that block a decision.
  3. Collect the minimum evidence needed for engagement inbox manager. Distinguish direct observations from assumptions and proxies.
  4. Execute the engagement inbox manager analysis or artifact using the domain checklist below; prefer specific outputs over generic best-practice lists.
  5. Prioritize actions by impact, confidence, effort and dependency. Identify what would falsify important assumptions.
  6. For external side effects, publishing, sending, spend changes, account changes or persistent writes, obtain authorization first.
  7. Finish with decision-ready output, evidence labels, open loops, and no more than three next-best skills.

Domain Checklist

  • Channel role
  • Audience behavior
  • Native format norms
  • Content/participation mix
  • Community response rules
  • Distribution loop
  • Measurement
  • Brand/safety escalation

Read the full file on GitHub · 75 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 7d ago First seen · 75 lines · 216 tokens per session scan A 38987151cbe2

Subscribe to this mod's changes

engagement-inbox-manager is a skill published in the GitHub repository iamwaqargulzar/Marketing-Agent-OS (5 stars, last pushed 8d ago), licensed Apache-2.0. It adds 216 tokens to every session and 913 once invoked, about $0.0011 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 2026-09-05.

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