influencer

influencer is a command for Claude Code from aaron-he-zhu/aaron-marketing-skills. It costs 39 tokens per session (1,121 once invoked), scanned A, original, Apache-2.0.

A workflow for influencer marketing, which means planning campaigns with online creators, from finding suitable creators through reporting results.

In plain words
What is it for?
Finding and evaluating creators, planning campaigns and budgets, preparing briefs, managing outreach, checking creator content, amplifying it, and reporting return on investment.
Why use it?
It organizes the campaign process and keeps scouting, outreach, content checks, and return tracking connected.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the aaron-marketing plugin — 120 skills, 8 commands, 7 hooks shipped together

Good fit Finding and evaluating creators, planning campaigns and budgets, preparing briefs, managing outreach, checking creator content, amplifying it, and reporting return on investment.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/aaron-he-zhu/aaron-marketing-skills/influencer
About the project

aaron-marketing-skills is a collection of 120 AI-agent skills covering marketing work such as brand narrative, search optimization, social media, email, advertising, influencer campaigns, and launches. Marketers and agent users can install it as a plugin, use its portable skills, or run its described bot team. The catalogue entries are components of this marketing workflow.

aaron-he-zhu/aaron-marketing-skills · 2,767 stars · on GitHub · aaronmarketing.ai

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.

Clone the repo
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills

Made for: Claude Code.

Or install aaron-marketing, the plugin that ships this one along with the rest of its 120 skills, 8 commands, 7 hooks.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/commands/aaron-he-zhu/aaron-marketing-skills/influencer"><img src="https://agentmods.dev/badge/commands/aaron-he-zhu/aaron-marketing-skills/influencer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,121 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 $0.00039 $0.01121
Opus 5 $0.00019 $0.00561
Sonnet 5 $0.00008 $0.00224
Haiku 4.5 $0.00004 $0.00112

Measured 10d ago against content hash fd32f37ee972, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

influencer 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 10d 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.

commands/influencer.md · 35 lines

How it starts

The opening of the file, as written. The whole thing — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Influencer Command

Run the influencer-marketing lifecycle along the STAR loop (Scout → Target → Activate → Report): understand the audience, find and score creators, plan and brief the campaign, run outreach and amplify, then track ROI. Skills score on the STAR framework (Suitability / Trust / Appeal / Return → SQS) and operate from the user's own data and project memory — keyed creator-analytics suites are never required; connectors only automate retrieval.

Route

Infer the phase from the goal (or honor --phase) and route to the matching skill:

  • Scout — audience-mapper (audience/niche modes), trend-spotter, influencer-discovery, fit-scorer (STAR Suitability); creator-registry dedupes candidates against the roster
  • Target — competitor-tracker, campaign-planner, brief-generator, budget-optimizer
  • Activate — outreach-manager, creator-content-auditor (STAR gate), contract-helper, content-amplifier (paid whitelisting / UGC repurpose modes) — resolve the carried opaque creator_ref through an authorized artifact or verified registry link, then consult the creator-registry projection (memory/creators/<aggregate-id>.md: contact path, last agreed rate, exclusivity, compliance history) before outreach or contracting; never derive the path from a raw handle
  • Report — landing-optimizer (post-click), performance-analyzer, roi-calculator (STAR Return), report-generator

Rules

  • Start where the goal sits in the funnel; do not force the full four-phase chain when the user only needs one stage.
  • creator-content-auditor is the pre-publish gate: any creator content goes through its STAR Trust check (FTC disclosure STAR-T1, claim integrity STAR-T2) before it ships.
  • For sponsored_content_gate, require disclosure status, claim evidence, and the governing brief. If any applicable evidence is unobserved, keep it Unknown and return NEEDS_INPUT/UNDECIDED/NOT_SCORED; missing evidence is not a veto. One independently verified veto maps to DONE_WITH_CONCERNS/FIX (Revisions Required); two or more map to DONE/BLOCK (Reject/Hold). A business BLOCK never becomes execution status: BLOCKED.
  • Return the audit inline by default. Only with explicit exact-write permission, a validator-clean v3 artifact, and a supported runtime writer may class: auditor-output be persisted to memory/audits/influencer/; otherwise identify that intended sink and ask for authorization.
  • memory/events/creators.ndjson is the roster history. Other skills submit authorized operation: propose events; creator-registry alone accepts/rejects or mutates canonical creator state. Run it when proposals are pending or a campaign cycle closes; memory/creators/ contains generated views.
  • Score creators/content/campaigns on STAR (Suitability/Trust/Appeal/Return → SQS); label every metric Measured / User-provided / Estimated; never fabricate reach or rates.
  • Tier 1 by default — works from user-provided data; connectors only automate retrieval. Compliance checks are guidance, not legal advice.
  • Follow each skill's Next Best Skill handoff; stop at the documented termination rules rather than auto-chaining the whole discipline.
  • Scope edge — creators vs adjacent lanes: "launch a product with creators" starts at campaign-planner while the launch itself runs on RAMP via /aaron-marketing:launch; "boost / repurpose this" is content-amplifier with paid execution handed to /aaron-marketing:ad; the always-on social calendar belongs to ECHO (social-calendar-builder); contract/rate/exclusivity records live in creator-registry, and any email opt-in evidence in consent-registry.
  • Paid creator whitelisting order: after the partner is confirmed, run contract-helper first for exact paid usage/whitelisting rights, then brief-generator for the governing brief. Only after the agreement/brief and draft asset exist, run creator-content-auditor (STAR-T1 disclosure + STAR-T2 claim integrity), followed by content-amplifier in its paid-planning mode. Then hand paid execution to /aaron-marketing:ad --phase activate, where ad-account-auditor gates before spend. Stop for explicit spend approval; no contract, creator audit, or amplification plan authorizes activation by itself.

Read the full file on GitHub · 35 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. 10d ago Changed fd32f37ee972
  2. 13d ago First seen · 35 lines · 39 tokens per session scan A 86f4dcdc806b

Subscribe to this mod's changes

influencer is a command published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 1,121 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 2026-08-30.