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 Smolevich/pet-project-atlas --skill content-plangit clone --depth 1 https://github.com/Smolevich/pet-project-atlasWrote 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/smolevich/pet-project-atlas/content-plan)<a href="https://agentmods.dev/skills/smolevich/pet-project-atlas/content-plan"><img src="https://agentmods.dev/badge/skills/smolevich/pet-project-atlas/content-plan/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/smolevich/pet-project-atlas/content-plan"><img src="https://agentmods.dev/badge/skills/smolevich/pet-project-atlas/content-plan.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 | $0.00080 | $0.01439 |
| Opus 5 | $0.00040 | $0.00720 |
| Sonnet 5 | $0.00016 | $0.00288 |
| Haiku 4.5 | $0.00008 | $0.00144 |
Grade A, and why
content-plan 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/atlas:content-plan
Implements the method on https://atlas.smolevich.com/content/keyword-clusters/. Read that page if you need the reasoning. This file is the procedure.
The working unit is a cluster: the phrasings one page can satisfy without splitting its answer. Not a keyword, not a topic. A page per keyword produces thin pages that compete with each other.
1. Collect the input
Ask for these and wait:
- What the project does, in the author's own words, and what a person can do inside it.
- The language the audience searches in. Not the interface language. It decides which results pages you check in step 4 and which heading set the drafts use in step 7.
- A Search Console export, if there is one — the Performance report, queries, CSV or TSV. Optional. Say plainly that without it steps 2 and 3 below run on guesses, and the plan is weaker.
If an export is given, read it and confirm the column you are using:
head -3 <export.csv>
wc -l <export.csv>
Sort by impressions, not by clicks. A query with impressions and no clicks is demand you already touch and lose — the cheapest cluster in the file.
2. Harvest phrasings, never invent them
Sources, in order of trust: support messages, reviews, forum and community threads, search autocomplete, the export.
Write down the exact words people used, clumsy ones included. The author's own vocabulary is the least reliable source in the room — the internal name for a feature is usually not what anyone types.
If the author gives you a phrase they made up, keep it out of the plan and say why.
3. Find the capability with no queries at all
Compare the harvested list against what people actually do inside the product.
A heavily used feature with zero queries in the export is a hole in the map, not proof that demand is absent. It usually means no page names it, so no page can be shown for it. Flag every such capability as a candidate cluster and mark it clearly as unvalidated.
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 First seen · 149 lines · 80 tokens per session scan A a19648871951
content-plan is a skill published in the GitHub repository Smolevich/pet-project-atlas (2 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 1,439 once invoked, about $0.0004 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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