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 agentmods add skills/seranking-planable/smm-skills/content-pattern-intelligencenpx skills add seranking-planable/smm-skills --skill content-pattern-intelligencegit clone --depth 1 https://github.com/seranking-planable/smm-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/seranking-planable/smm-skills/content-pattern-intelligence)<a href="https://agentmods.dev/skills/seranking-planable/smm-skills/content-pattern-intelligence"><img src="https://agentmods.dev/badge/skills/seranking-planable/smm-skills/content-pattern-intelligence.svg" alt="Measured on agentmods" 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 | $0.00160 | $0.04517 |
| Opus 5 | $0.00080 | $0.02259 |
| Sonnet 5 | $0.00032 | $0.00903 |
| Haiku 4.5 | $0.00016 | $0.00452 |
Grade A, and why
content-pattern-intelligence 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 5d 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 — 451 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content pattern intelligence
Look at what's actually working — then tell the user why, and what to try next.
This skill analyzes top posts across three performance lenses, finds patterns in the content itself (format, hook, topic, tone, structure), and translates them into specific, testable hypotheses for future posts.
This is not a performance report. It's a content brief grounded in data.
Step 0: Detect input mode
Mode A — Planable connector User has Planable connected and wants to pull live post data.
Mode B — CSV upload User has uploaded a CSV export with post-level data (text, date, platform, metrics).
How to detect:
- File uploaded → Mode B
- Mentions "CSV", "export", "file", "spreadsheet" → Mode B
- Mentions workspace name, client, or Planable → Mode A
- Unclear → ask: "Do you have a CSV with your post data, or should I pull it from Planable?"
Mode A: Planable connector
Step 1: Gather inputs
- Workspace / client — which workspace to analyze
- Platform(s) — default to all; narrow if requested
- Date range — default to last 60–90 days (needs enough posts to find patterns; warn if fewer than 15 posts available)
Step 2: Fetch data — with Instagram-safe refresh logic
Instagram metrics sync is async and slow. Always follow this sequence to avoid timeouts.
Always call get_post_metrics with exactly one pageId per request. Multi-page calls compound timeouts — never bundle multiple pages into a single call.
Step 2a: Read first, check freshness
list_workspaces → find workspaceId
list_pages(workspaceId) → get pageIds
get_page_metrics(workspaceId, pageIds, startDate, endDate)
For each page in the response, check lastMetricAt (the timestamp of the last successful metrics fetch).
- If
lastMetricAtis within the last 3 hours — data is fresh. Skip the refresh entirely. Proceed to Step 2c. - If
lastMetricAtis older than 3 hours or missing — data is stale. Proceed to Step 2b.
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.
- 5d ago First seen · 451 lines · 160 tokens per session scan A 6f90c675c48c
content-pattern-intelligence is a skill published in the GitHub repository seranking-planable/smm-skills (3 stars, last pushed 2mo ago), licensed MIT. It adds 160 tokens to every session and 4,517 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 2026-08-31.
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