influencer-marketing

influencer-marketing is a skill for Claude Code from iamwaqargulzar/Marketing-Agent-OS. It costs 39 tokens per session (977 once invoked), scanned A, a copy of impeccable, Apache-2.0.

A workflow for planning creator and influencer programs from audience mapping and discovery through outreach, agreements, content review, promotion, and return measurement.

In plain words
What is it for?
Use it to design creator campaigns, manage collaboration steps, review sponsored content, and measure campaign results.
Why use it?
It organises the many stages of an influencer program so planning does not stop at finding creators.

Skill for Claude Code

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

Part of the marketing-agent-os plugin — 175 skills shipped together

Good fit Use it to design creator campaigns, manage collaboration steps, review sponsored content, and measure campaign results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/iamwaqargulzar/marketing-agent-os/influencer-marketing
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 influencer-marketing
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 175 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 influencer-marketing

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/iamwaqargulzar/marketing-agent-os/influencer-marketing"><img src="https://agentmods.dev/badge/skills/iamwaqargulzar/marketing-agent-os/influencer-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 977 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 61% copy Near-identical to another mod 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 $0.00039 $0.00977
Opus 5.5 $0.00016 $0.00391
Sonnet 5.5 $0.00008 $0.00195
Haiku 4.5 $0.00004 $0.00098

Measured 14d ago against content hash 23072e486311, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

influencer-marketing 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 14d 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.

Origin

This is a copy

61% identical to impeccable — 318 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/influencer-marketing/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Influencer Marketing

Quick Start

Use this skill for influencer marketing. 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 influencer marketing 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 influencer marketing. Distinguish direct observations from assumptions and proxies.
  4. Execute the influencer marketing 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.

Telegram channel placements

For a sponsored Telegram post, separate direct admin placements from the official ad product and check each one's current rules. Assess dated post-view evidence, audience language/topic, channel age, anomalous growth, placement terms, and distribution of comparable post reach; subscribers are not guaranteed impressions and views are not unique people. Label third-party reach/pricing benchmarks as proxies. Propose a capped pilot with disclosures, approved assets, tracking limits, and delivered-placement receipts before extrapolating ROI.

Read the full file on GitHub · 86 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. 14d ago Changed · +6 lines · +7 tokens per session 23072e486311
  2. 22d ago Changed · +4 lines · +3 tokens per session 693b900b1a3c
  3. 2mo ago First seen · 76 lines · 29 tokens per session scan A d4538f044fb3

Subscribe to this mod's changes

influencer-marketing is a skill published in the GitHub repository iamwaqargulzar/Marketing-Agent-OS (8 stars, last pushed 3d ago), licensed Apache-2.0. It adds 39 tokens to every session and 977 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 61% identical to impeccable, differing in 318 lines, and is treated as a copy.

Related

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