Agent skill · Documentation

platform-norm-profiler

Use when the user asks to "build the norm card for this platform", "what are the char limits and visible-fold cutoffs here", "is the LinkedIn link-in-first-comment thing documented or folklore", or "which of our platform cards are stale"; maintains the dated, versioned per-platform norm cards in the references/platforms/ pack — char limits, visible-fold cutoffs, hashtag norms, format/aspect specs, link and first-comment placement, disclosure-label mechanics, algorithm emphases (e.g. 小红书 search+saves weighting) — every row labeled platform-documented (official doc, Measured) or Estimated-folklo

aaron-he-zhugithub.com/aaron-he-zhuGitHub ↗
claude-codeApache-2.0
Install
npx skills add aaron-he-zhu/aaron-marketing-skills --skill platform-norm-profiler --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 12 KB
Bundled scripts: none
Version: 19.1.0
Requires: Claude Code and compatible agent-skill hosts
Path: social/explore/platform-norm-profiler/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,508
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Platform Norm Profiler Maintains the dated, versioned per-platform norm cards the Craft phase drafts against — char limits, visible-fold cutoffs, hashtag norms, format/aspect specs, link and first-comment placement, disclosure-label mechanics, and algorithm emphases — every row labeled platform-documented (Measured, official doc) or Estimated-folklore (named source) with a last-verified date. It feeds four [ECHO](../../../references/echo-benchmark.md) sub-items directly: the three C dated-norm-card items — platform adaptation, never verbatim cross-posting (C3), format specs citing the dated card (C4), and link/first-comment placement per the card (C9) — plus the E rule-digest-current item (E4). [social-quality-auditor](../../host/social-quality-auditor/SKILL.md) judges those items against the cards this skill keeps fresh. The anti-staleness rule is the whole point: **a norm card older than its review-by date is flagged, not trusted.** **Scope guard**: this skill maintains norm cards only. It does NOT pick which channels to run ([channel-portfolio-planner](../channel-portfolio-planner/SKILL.md)), write brand voice rules (`voice-dossier-builder`), draft posts ([social-creative-buil

What's inside
Steps it walks through
  1. Quick Start
  2. Skill Contract
  3. Handoff Summary
  4. Data Sources
  5. Instructions
  6. Save Results
  7. Reference Materials
  8. Next Best Skill
More from aaron-marketing-skills
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About this skill
What does the platform-norm-profiler skill do?

Use when the user asks to "build the norm card for this platform", "what are the char limits and visible-fold cutoffs here", "is the LinkedIn link-in-first-comment thing documented or folklore", or "which of our platform cards are stale"; maintains the dated, versioned per-platform norm cards in the references/platforms/ pack — char limits, visible-fold cutoffs, hashtag norms, format/aspect specs, link and first-comment placement, disclosure-label mechanics, algorithm emphases (e.g. 小红书 search+saves weighting) — every row labeled platform-documented (official doc, Measured) or Estimated-folklo

How do I install it?

Run `npx skills add aaron-he-zhu/aaron-marketing-skills --skill platform-norm-profiler --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From aaron-he-zhu/aaron-marketing-skills, a repository with 2,508 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going