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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skillsnpx agentmods add skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-plannerWrote 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/skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-planner)<a href="https://agentmods.dev/skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-planner"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-planner/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/skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-planner"><img src="https://agentmods.dev/badge/skills/aaron-he-zhu/aaron-marketing-skills/bid-strategy-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00127 | $0.02422 |
| Opus 5 | $0.00063 | $0.01211 |
| Sonnet 5 | $0.00025 | $0.00484 |
| Haiku 4.5 | $0.00013 | $0.00242 |
Grade A, and why
bid-strategy-planner 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bid Strategy Planner
Chooses the bid strategy for a paid campaign — tCPA, tROAS, max-conversions, or manual CPC — sets the starting target from the account's own conversion history, groups campaigns into a bid portfolio, and lays out a learning-phase entry plan. This is the plan skill that sets the ROAS S (Spend-efficiency) bidding lever; it does not allocate the budget (budget-optimizer), does not adjust pacing in-flight (budget-pacing-monitor), and does not score the account or run the vetoes (ad-account-auditor).
Quick Start
Pick a bid strategy for [campaign]: DR goal, past 30 days $42 CPA at 90 conversions/mo
Set a starting tROAS target for [campaign] — history is 3.8x ROAS, goal is 4.5x
Group these 4 search campaigns into a bid portfolio and plan the learning-phase entry
Output: a named bid strategy with rationale, the starting target and how it was derived (labeled Measured / User-provided / Estimated), a portfolio grouping map, and a learning-phase entry/exit plan.
Skill Contract
- Reads: ROAS profile (
direct-response|prospecting|incremental-profit), conversion history (CPA / ROAS + conversion volume from the user's own GA4/ecommerce export), current bid strategy if restructuring, campaign set + budgets, and any minimum-daily-conversion or account-structure constraints. Connector data via~~web analytics/~~ecommerce(own-data manual export) when available. - Writes: a bid-strategy recommendation (strategy + starting target + portfolio map + learning-phase entry plan) and a reusable handoff summary. Save path:
memory/ad/bid-strategy-planner/YYYY-MM-DD-<campaign>.md. - Promotes: the chosen strategy, the locked starting target, and the portfolio grouping — propose durable decisions as
pending-decisionitems inmemory/open-loops.md; do not writememory/decisions.mddirectly. - Done when:
- One bid strategy is named with a rationale tied to the goal and the conversion-volume threshold.
- The starting target is stated with its derivation, and every input metric is labeled Measured / User-provided / Estimated.
- A learning-phase entry plan names the conversions-to-exit estimate and the do-not-touch window.
- Primary next skill: ad-account-auditor — scores the campaign against ROAS (the S lever + premature-scaling guardrail) before launch.
What ships with it
1 file 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.
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 0df1deacc659
- 13d ago First seen · 102 lines · 127 tokens per session scan A fa4ec97d9ee5
bid-strategy-planner is a skill published in the GitHub repository aaron-he-zhu/aaron-marketing-skills (2,767 stars, last pushed today), licensed Apache-2.0. It adds 127 tokens to every session and 2,422 once invoked, about $0.0006 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 skills, from other repositories
geo-visibility-check
One-shot GEO audit: does your brand appear in Claude, ChatGPT, and Gemini answers for the buyer questions that matter? Runs a prompt panel through the engines with citation tracing and reports per-prompt verdicts, who wins instead, and which sources the answers come from.
geo-optimizer-skill
Run geo audit first. It scores the site 0–100 across 8 categories and generates a prioritized action list.
geo-loop
Run one bounded eGEOagents loop iteration over a workspace domain - read the charter and fresh collector data, do ONE unit of work, write substrate artifacts, append one Timeline entry and one LOG line. Use for loop mode, /geo:loop, scheduled GEO runs, or continuous monitoring.
content-scoring
Score content against the 10 GEO criteria with evidence and prioritized fixes. Use when users ask to score, rate, evaluate, or estimate ranking strength.
competitive-analysis
Analyze AI-search competitors for a query and recommend ranking strategy. Use when users ask competitor analysis, who ranks, or competitive landscape.
schema-generator
Generate JSON-LD schema markup for pages and content types with an implementation checklist. Use when users ask for schema, structured data, rich snippets, or markup.