influencer-strategy

influencer-strategy is a skill for Claude Code from anhnguyen0905/codex-mcp. It costs 67 tokens per session (1,550 once invoked), scanned A, original, MIT.

A planning guide for influencer marketing: choosing creators, agreeing on collaborations, and measuring results. Influencers are people whose online audiences may affect what others discover or buy.

In plain words
What is it for?
Use it to choose creators by audience and authenticity, plan creator tiers and budgets, prepare briefs and contracts, and measure reach, cost, engagement, and campaign performance.
Why use it?
It helps select creators based on audience fit and trust rather than follower count alone, while clarifying costs, creative control, and usage rights.

Skill for Claude Code

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

Part of the codex-flow plugin — 65 skills, 2 commands, 1 MCP server shipped together

Good fit Use it to choose creators by audience and authenticity, plan creator tiers and budgets, prepare briefs and contracts, and measure reach, cost, engagement, and campaign performance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anhnguyen0905/codex-mcp/influencer-strategy
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 anhnguyen0905/codex-mcp --skill influencer-strategy
Clone the repo
git clone --depth 1 https://github.com/anhnguyen0905/codex-mcp

Made for: Claude Code.

Or install codex-flow, the plugin that ships this one along with the rest of its 65 skills, 2 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 influencer-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/influencer-strategy/github.svg)](https://agentmods.dev/skills/anhnguyen0905/codex-mcp/influencer-strategy)
Your own site
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/influencer-strategy"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/influencer-strategy/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-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/influencer-strategy"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/influencer-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,550 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 $0.00067 $0.01550
Opus 5 $0.00034 $0.00775
Sonnet 5 $0.00013 $0.00310
Haiku 4.5 $0.00007 $0.00155

Measured 11d ago against content hash 09411f1fc23e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

influencer-strategy 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 11d 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/influencer-strategy/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Influencer Strategy (creator selection, contracting, measurement)

Tiers are roles, not sizes

nano  (~1k-10k)    cheapest per post, high comment intimacy; local/niche proof and cheap volume
                   testing of angles. Most ops overhead per unit of reach.
micro (~10k-100k)  workhorse: real topical authority, negotiable, enough volume to A/B creators.
mid   (~100k-500k) meaningful single-post reach with retained community trust; anchors a wave.
macro/celebrity    reach, credibility transfer, PR value. Priced like media, not word of mouth;
                   low CPE, weaker comment-level trust, key-person risk.

Bands differ by platform and market — re-cut them from your own data; the tier's job is the point. Portfolios beat single tiers: macro/mid for reach and legitimacy, micro/nano for coverage, repeatability and cheap creative learning.

Select on fit, not follower count

Rank on audience overlap with the target (geo, language, age, interest — from the creator's own audience export, not a guess) · topical authenticity (do they use the category unpaid?) · comment substance and sentiment · brand-deal density, since back-to-back sponsorships convert poorly · brand-safety history. Follower count only sets the price band; an audience 70% outside your market is expensive at any CPM.

CPM / CPE as planning inputs

CPM = fee / (expected impressions / 1000)
CPE = fee / expected engagements   ← define engagement: likes+comments+shares+saves
CPV = fee / expected views         ← state the platform's view definition; they differ
expected impressions ≈ MEDIAN views of the creator's last N comparable organic posts

Use recent medians, never peaks and never follower count. Sanity-check the resulting CPM against your paid CPM for the same placement. These are estimates: pay on deliverables and terms, and negotiate a make-good clause if delivered reach lands far below the stated median.

Brief, creative freedom, and contract terms

Give only the non-negotiables — single message, mandatory and prohibited claims, hook window, CTA and link/code, delivery spec. The creator owns format, voice, script and edit; that native voice is what you are buying, and word-for-word scripting reads as an ad and loses the trust you paid for. Approve a concept or outline instead of line-editing. The contract must then fix:

Read the full file on GitHub · 117 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. 11d ago First seen · 117 lines · 67 tokens per session scan A 09411f1fc23e

Subscribe to this mod's changes

influencer-strategy is a skill published in the GitHub repository anhnguyen0905/codex-mcp (3 stars, last pushed today), licensed MIT. It adds 67 tokens to every session and 1,550 once invoked, about $0.0003 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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