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.
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.
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skillsWrote 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.
[](https://agentmods.dev/commands/aaron-he-zhu/aaron-marketing-skills/influencer)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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_refthrough 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-auditoris 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 returnNEEDS_INPUT/UNDECIDED/NOT_SCORED; missing evidence is not a veto. One independently verified veto maps toDONE_WITH_CONCERNS/FIX(Revisions Required); two or more map toDONE/BLOCK(Reject/Hold). A businessBLOCKnever becomes executionstatus: 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-outputbe persisted tomemory/audits/influencer/; otherwise identify that intended sink and ask for authorization. memory/events/creators.ndjsonis the roster history. Other skills submit authorizedoperation: proposeevents;creator-registryalone 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-helperfirst for exact paid usage/whitelisting rights, thenbrief-generatorfor the governing brief. Only after the agreement/brief and draft asset exist, runcreator-content-auditor(STAR-T1 disclosure + STAR-T2 claim integrity), followed bycontent-amplifierin its paid-planning mode. Then hand paid execution to/aaron-marketing:ad --phase activate, wheread-account-auditorgates before spend. Stop for explicit spend approval; no contract, creator audit, or amplification plan authorizes activation by itself.
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.
- 10d ago Changed fd32f37ee972
- 13d ago First seen · 35 lines · 39 tokens per session scan A 86f4dcdc806b
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.
Other commands, from other repositories
geo:loop
Run one bounded loop iteration over a workspace domain - read the charter and fresh collector data, do ONE unit of work, write substrate artifacts, close the run.
geo
Full GEO optimization pipeline - analyze, rank, rewrite, and generate schema for any URL or content.
geo:optimize
Optimize a local content file for GEO without full audit.
geo:audit
Analyze content for GEO optimization opportunities without making changes.
geo:batch
Process multiple content files in a folder.
geo:compete
Analyze competitive landscape for a query or topic.