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 wolfenazz/YzPzCode --skill social-media-dashboardgit clone --depth 1 https://github.com/wolfenazz/YzPzCodeWrote 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/wolfenazz/yzpzcode/social-media-dashboard)<a href="https://agentmods.dev/skills/wolfenazz/yzpzcode/social-media-dashboard"><img src="https://agentmods.dev/badge/skills/wolfenazz/yzpzcode/social-media-dashboard.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 | $0.00130 | $0.01439 |
| Opus 5 | $0.00065 | $0.00720 |
| Sonnet 5 | $0.00026 | $0.00288 |
| Haiku 4.5 | $0.00013 | $0.00144 |
Grade A, and why
social-media-dashboard 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 4d 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.
This is a copy
100% identical to social-media-dashboard — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Dashboard Skill
Produce a single-screen, creator-facing social media analytics dashboard.
Workflow
- Read the active DESIGN.md (injected above). Colors, typography, spacing, radii, and component styling all come from it. Do not invent new tokens; do not hard-code brand colors of the platforms — let the DESIGN.md carry the visual identity, and reference platforms only by name and monogram.
- Identify which platforms the brief calls out. Default to X / LinkedIn / YouTube / Instagram if unspecified. Keep the platform switcher to a single row, max 5 entries.
- Generate plausible data, never
Metric A / Metric Bplaceholders. Pick a creator persona (default: "AI / design indie creator") and derive consistent numbers across the page — e.g. follower counts on the switcher must match the KPI row when X is selected. - Lay out the page top-to-bottom:
- Header bar: brand mark + section label ("ANALYTICS"), a dark/light toggle, time-range tabs (7D · 30D · 90D · YTD), and a creator avatar block on the right.
- Hero strip: a one-sentence summary in display type ("You shipped 14 posts on X this week."), one supporting line of metadata, and two CTAs ("Export report", "New post →").
- Ask bar: a single-line input styled as a search field, with ghost-text suggestions ("top performing last week", "comments from verified accounts").
- Platform switcher: 4 cards in one row, each with platform
monogram, name, follower count, and a
+X.XK this weekdelta. The active platform uses an elevated surface from DESIGN.md. - KPI row: 4 cards — Followers · Engagement Rate · Likes (7D) · Reposts (7D). Each card has a label (uppercase, label-md), a big value (display or headline-lg), a delta vs prior period, and a small footnote ("vs. 4.4% last week", "Aug 9–17 · 14 posts").
- Main grid (2/3 + 1/3):
- Left: Follower Growth · 30D — a full-width inline SVG line chart with a soft area fill underneath, axis ticks at start / midpoint / end, and two labelled annotation dots ("Newsletter drop +842", "Viral thread +1.2K").
- Right: Top Post · This Week — a card showing the rendered post (avatar, handle, post body, optional 16:9 media block), with a header tag "click-through rate 5.6%" in the DS accent.
- Lower grid (1/2 + 1/2):
- Trending topics on this platform: 5–7 chip-style rows with topic name + post count + 24h delta sparkline (10 polyline points, no labels).
- Top comments: 3 cards, each with avatar, handle (verified
check if relevant), comment body (2 lines max, ellipsised), and
a small
❤ 312 · 💬 18row in muted text.
- Write one self-contained HTML document:
<!doctype html>through</html>, CSS in one inline<style>block.- CSS Grid for page-level layout; Flexbox inside cards.
- Semantic HTML:
<header>,<main>,<section>,<article>. - Tag each logical region with
data-od-id="slug"for comment mode:header,hero,ask,platform-switcher,kpis,follower-growth,top-post,trending,top-comments.
- Charts: inline SVG only, no JS libraries.
- Line chart:
<path>for the curve, a second<path>with low-alpha fill for the area, two<circle>annotation dots with text labels. - Sparklines:
<polyline>with 10 points, no axes, ~16px tall. - Use the DS accent for highlights and the DS
on-surface-variantfor muted text. Accent appears at most three times on the page.
- Line chart:
- Self-check:
- Every color resolves to a DESIGN.md token (or a documented
rgba(token, alpha)for glass surfaces). - Numbers are internally consistent (switcher follower count matches the active platform's KPI).
- Header bar and hero strip are sticky; main content scrolls.
- Density follows the DS mood: glass / cosmic DSes get more breathing room and ambient glow on the active platform; clean / corporate DSes tighten gaps and drop the glow.
- Every color resolves to a DESIGN.md token (or a documented
What ships with it
2 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.
- 4d ago First seen · 119 lines · 130 tokens per session scan A 8755632fff86
social-media-dashboard is a skill published in the GitHub repository wolfenazz/YzPzCode (13 stars, last pushed 3d ago), licensed Apache-2.0. It adds 130 tokens to every session and 1,439 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to social-media-dashboard, differing in 0 lines, and is treated as a copy.
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