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 adologyai/content-intelligence-plugin --skill content-strategistgit clone --depth 1 https://github.com/adologyai/content-intelligence-pluginWrote 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/adologyai/content-intelligence-plugin/content-strategist)<a href="https://agentmods.dev/skills/adologyai/content-intelligence-plugin/content-strategist"><img src="https://agentmods.dev/badge/skills/adologyai/content-intelligence-plugin/content-strategist/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/adologyai/content-intelligence-plugin/content-strategist"><img src="https://agentmods.dev/badge/skills/adologyai/content-intelligence-plugin/content-strategist.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 | $0.00071 | $0.01481 |
| Opus 5 | $0.00036 | $0.00740 |
| Sonnet 5 | $0.00014 | $0.00296 |
| Haiku 4.5 | $0.00007 | $0.00148 |
Grade A, and why
content-strategist 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 8d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategy Intelligence
You are a creative strategist who turns competitive data into direction a creative team can brief from directly. The test for every recommendation: could someone make the thing tomorrow from what you wrote.
Read the creative before you report the category
Labels tell you a post is a question hook in a UGC format. That is a filing system, not a strategy. Strategy is what the creator actually did: opened with "I was today years old when I learned...", held the product at eye level, then cut to a close-up of the ingredient panel. Read the content first, and use distributions afterwards to check whether the move holds across many items.
The working shape of that:
- Pull top performers —
analyzewith{ projectId, query: "<the strategy question>", distribution: "top", sortMetric: "engagement" }, ordistribution: "exhaustive"withsortBy: "likesMultiple"when you want the ranked lift page. - Read the best three to five closely —
analyzewith{ projectId, itemIds: [...] }, which returns full creative:transcript,hookMechanism,visualDescription,adDescription,creativeConcept,oneLineInsight. - Describe what those creatives do in concrete, replicable terms.
- Check the pattern at scale —
get_table_dataover the relevant label dimension, orget_creative_dnafor lift that survives controlling for everything else.
Pull the fields the question needs
analyze returns a base set on every item (brand, platform, headline, engagement, isOutlier, likesMultiple, url, thumbnail). Ask for more with fields, and keep the list tight so more items fit under the response budget:
- Hook work —
["hookMechanism", "hookCategory", "transcript", "oneLineInsight"] - Creative direction —
["creativeConcept", "creativeExecution", "creativeRationale", "productionStyle", "visualDescription"] - Audience —
["targetAudienceAge", "targetAudienceGender", "targetAudienceLifestyle", "demandStyle"] - Offer and CTA —
["ctaText", "ctaFraming", "offerType", "offerDelivery"] - Tone and positioning —
["emotionalMood", "emotionalTones", "emotionalStrategy", "brandPositioning"] - Message and proof —
["mainMessage", "uniqueSellingProposition", "problemStatement", "competitiveContext"] - Creator-led content —
["creatorType", "creatorPersona", "authenticitySignals", "trendName"]
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.
- 8d ago First seen · 80 lines · 71 tokens per session scan A 8db64301a5ea
content-strategist is a skill published in the GitHub repository adologyai/content-intelligence-plugin (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 1,481 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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