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Analytics interpreter

Skill moses607/socialforge/skills/analytics-interpreter

SocialForge — 17 open-source Claude skills that turn any capable model into an AI social-media growth agency: competitor analysis, hooks, viral scripts, repurposing, trends, engagement, and an orchestrator. MIT.

Install
npx -y skills add moses607/socialforge --skill analytics-interpreter

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What its author says it does

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Turns raw platform analytics into a funnel diagnosis instead of a data dump. It reads every metric as evidence about ONE stage of the growth funnel, locates the single biggest leak, and prescribes the fix. Use when someone shares metrics/insights, asks "what do these numbers mean", "why are my views low", or "why isn't this growing". Works with any capable model.

SKILL.md

4.6 KB, as published. Nobody here has run it

Analytics Interpreter

Metrics are not a scoreboard; they are a diagnostic X-ray of one funnel: Distribution -> Hook -> Body -> Conversion -> Amplification. Every number is evidence about exactly one stage. Growth stalls because ONE stage leaks, not because "everything is bad." Your job is not to summarize the dashboard — it is to name the single leak that, if fixed, unlocks the most upside, and ignore everything else. Vanity metrics (likes, followers, total views) describe the past; rate metrics (hook rate, retention, saves-per-view) predict the future. Diagnose rates.

1. Map each metric to what it REVEALS

  1. Impressions / reach -> DISTRIBUTION. How many the algorithm tested you on. Low reach = the algorithm killed it early (usually a hook or early-retention problem, not a reach problem).
  2. Hook rate / 3s-view rate (views ÷ impressions) -> HOOK QUALITY. Below ~30% weak, 30-45% average, 45%+ strong. This is the first gate.
  3. Average watch time & retention curve -> BODY/CONTENT QUALITY. For short video, watch-time ratio (avg watch ÷ length) above ~0.8 is strong; full watch or rewatch (>1.0) triggers pushes.
  4. CTR (on titles/thumbnails, YouTube/blogs) -> PACKAGING. 2-4% baseline, 5%+ strong, sub-2% weak.
  5. Saves & shares -> VALUE + IDENTITY. THE growth signals. Save = "useful to future me." Share = "this represents me." Target saves+shares ≥ 1-2% of views.
  6. Follows-per-view -> PROFILE + CONTENT FIT. Are viewers converting to subscribers.
  7. Comments -> RESONANCE. Emotional or debate-worthy enough to react.

2. Read the retention curve — the drop tells you what to fix

  1. Cliff in first 1-3s -> hook fails / mismatch between hook promise and thumbnail-or-first-frame. Fix the opening.
  2. Steady slow decline -> normal; healthy content loses viewers gradually. Leave it.
  3. Sudden mid-video drop -> a specific dead moment: slow setup, tangent, no payoff yet. Cut it.
  4. Flat / rising line -> loops, open loops, or payoff pulling viewers through. Do MORE of this.
  5. Compare the CURVE, not the average — two videos with equal avg watch time can have opposite fixes.

3. Find the ONE leak, then stop

  1. Walk the funnel top-down. Find the FIRST stage below benchmark — that is the binding constraint.
  2. Reach low + hook rate low -> HOOK leak. Reach low + hook fine -> topic/niche-fit or account-trust leak.
  3. Hook fine + retention drops -> BODY leak (pacing/payoff). Hook + retention fine but low follows/saves -> CONVERSION leak (weak CTA, no reason to follow, no takeaway to save).
  4. Everything decent but flat growth -> AMPLIFICATION leak (not shareable/saveable — no identity or utility payload).
  5. Name exactly ONE leak. Fixing the top leak moves everything downstream; fixing downstream while the top leaks wastes effort.

Output template

FUNNEL DIAGNOSIS
- Distribution (reach/impressions): [n] — [healthy/leaking]
- Hook (3s / hook rate): [n]% — [vs ~40% benchmark]
- Body (retention / avg watch): [n]% — curve shape: [cliff/decline/flat]
- Conversion (follows-per-view, saves): [n] — [healthy/leaking]
- Amplification (shares+saves per view): [n]% — [healthy/leaking]

BIGGEST LEAK: [stage] — [one sentence why, citing the number]

THE FIX: [one concrete change to make on the next post]
Expected signal to watch: [which metric should move]

Platform variants

  • TikTok/Reels/Shorts: hook rate + watch-time ratio dominate; saves/shares are the amplifiers.
  • YouTube long-form: CTR × avg-view-duration is the algorithm's core; a great CTR with low retention gets throttled.
  • Instagram feed/carousels: saves and sends are the ranking signal; reach follows them.
  • X/LinkedIn: profile clicks, dwell/expands, and reposts over raw impressions.

Rules

  • Name ONE leak. A diagnosis with three problems is not a diagnosis.
  • Always diagnose RATES; never conclude from raw totals or follower count.
  • Read the retention CURVE shape, not just average watch time.
  • Treat saves and shares as the leading indicators of reach — reach is the lagging result.
  • Low reach is almost never a "reach problem" — it is the algorithm reacting to a hook or early-retention leak.
  • If a benchmark is unknown, compare the post against the account's own median, never against zero.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.