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.
npx skills add SupercmoHQ/superCMO-skills --skill planning-campaignsgit clone --depth 1 https://github.com/SupercmoHQ/superCMO-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/skills/supercmohq/supercmo-skills/planning-campaigns)<a href="https://agentmods.dev/skills/supercmohq/supercmo-skills/planning-campaigns"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/planning-campaigns/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/supercmohq/supercmo-skills/planning-campaigns"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/planning-campaigns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00164 | $0.01964 |
| Opus 5 | $0.00082 | $0.00982 |
| Sonnet 5 | $0.00033 | $0.00393 |
| Haiku 4.5 | $0.00016 | $0.00196 |
Grade A, and why
planning-campaigns 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Campaign planning
Decide what ads to make next, write each one down as a concept a producer can build from directly, and build the ones the user approves.
Nothing is generated before the plan is approved. Everything up to the plan is planning; building is a separate decision the user makes at the end, concept by concept.
Workflow
Step 1: Scope the run
Ask once, bundled into a single message, always with a free-text way out. Skip any of these the brief already answers.
| Ask | When | How |
|---|---|---|
| The product | Always. | A URL or a photo. Where they name several, ask whether it is one campaign for all of them or one each. |
| The objective | The brief doesn't say. | Offer awareness, consideration and conversion, and a way to type another. |
| The competitors | The brief names none. | A name and a website for each. Where the user doesn't know, say you will let the research propose them and confirm before it reads anything. |
| The market | The brief names none and the site implies none. | Offer the likely markets, and a way to type another. |
| How deep to go | The brief doesn't say. | Offer the quick scan first and recommend it; say the deeper option roughly doubles what is watched, and costs accordingly. |
Ask them here, and pass the answers down. Don't go on without the product.
Step 2: Gather the context
Open the run's folder first. Everything this run produces lives in one place:
campaigns/<date-time> under ./supercmo-files. Where a folder for this minute already exists, add -2, -3, … rather than writing into it.
The plan is built from four inputs. Collect each one; skip one only where the brief already carries what it would return.
Every answer from Step 1 goes into the request that starts each skill — the product, the objective, the competitors, the market, the depth. A skill that receives them treats its own scoping questions as already answered; one that doesn't will guess. Where something is still unsettled, have the skill report it back rather than assume, and bring it to the user here.
What ships with it
3 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.
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.
- 11d ago First seen · 129 lines · 164 tokens per session scan A 3676bdc2968d
planning-campaigns is a skill published in the GitHub repository SupercmoHQ/superCMO-skills (38 stars, last pushed 14d ago), licensed Apache-2.0. It adds 164 tokens to every session and 1,964 once invoked, about $0.0008 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.
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