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SKILL verified MIT Self-run

Retention Audit

skill-yaxeen-storytelling-skills-retention-audit · by yaxeen

Use when diagnosing why a published video underperformed — reading a YouTube retention graph, comparing a weak video against a winner, or mapping audience drop-off points to script beats. For writing the next script, use storytelling-hooks or long-form-youtube.

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Install

$ agentstack add skill-yaxeen-storytelling-skills-retention-audit

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Security review

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No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

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About

Retention Audit

  • A retention graph is the story's autopsy: every drop is a moment the script broke a promise, every spike is a beat viewers rewound to see again.
  • Audit by zones, not by staring at the whole line — each zone has its own failure causes and its own fix.
  • Always diagnose against a baseline: the same channel's best comparable video (same length/format). Absolute numbers mislead; the gap between winner and loser is the finding.
  • Built on the six levers — see storytelling-hooks. Recap: 1. Curiosity gap · 2. Emotional mirror · 3. Conflict engine · 4. Relatability · 5. Pattern + surprise · 6. Three-act.

When to Use

  • A video got clicks but died (decent CTR, low average view duration).
  • YouTube stopped recommending a video after its first test batch.
  • Comparing a flop against the channel's winners to find what broke.
  • Any niche; needs the retention graph (screenshot is fine), the script or beat outline, and ideally one winner's graph.

Intake (Before Auditing)

  • Get: this video's retention graph + length, the script or beat list with rough timestamps, CTR and impressions if available, and a winner's graph from the same channel/format.
  • Also get the thumbnail + title + the video's first frame — the #1 retention killer lives in that triangle, not in the script.
  • Missing the winner baseline? Use the gray "typical retention" band as a weak substitute and say so.
  • No graph, no audit. Never estimate or invent retention numbers — ask for the screenshot; offer only hypothesis-level guesses clearly labeled as such.

The Five Zones (Quick Reference)

| Zone | Where | Healthy sign | Failure means | |------|-------|--------------|---------------| | Cliff | 0:00–0:30 | ≥65–70% still watching | packaging↔opening mismatch (confirm-the-click failure) | | Intro | 0:30–2:00 | slope flattening | throat-clearing, promise not restated, stakes missing | | Body | 2:00–sag | tracks/above typical band; small spikes | a loop closed without opening the next; pacing monotone | | Sag | ~40–60% of runtime | a visible re-hook bump or held line | no planned re-hook; mid-video drift | | End | last 10% | gentle taper | fine unless a cliff — outro started too early |

  • Timestamp boundaries assume ~10–12 min videos; scale the intro/body boundaries proportionally for other lengths — the 0:00–0:30 cliff stays fixed regardless of runtime.
  • Spikes = rewatch beats. Mark them: those are the moments that worked — reuse their structure in future scripts.
  • The most common pattern: steep cliff + healthy body = the video was fine, the first minute betrayed the click. Fix packaging/opening, not the story.

Audit Workflow

  1. Overlay the comparison. Note the winner-vs-loser gap at 0:30, 1:00, 2:00. If the gap is born in the first minute, the diagnosis is almost never "bad content."
  2. Check the click triangle. Thumbnail promise vs title promise vs actual first frame/line. Any mismatch = the cliff's cause. (Winner channels show the same world in thumbnail and frame one.)
  3. Map drops to beats. Put the script's beats on the timeline; for each visible dip, name the beat that was playing. Ask: did this beat close a loop without opening one? Sag without a re-hook? Tension the audience didn't come for?
  4. Check the channel formula. Compare the flop's premise against the winners' shared pattern (subject type, resolution type, emotional promise) — use channel-formula to extract it if it isn't written down yet. A technically good story that breaks the channel's core promise still dies — audience expectation beats craft.
  5. Mark the spikes. List rewatched moments and what structural move each used.
  6. Deliver findings — for each: timestamp zone, what the graph shows, the script beat responsible, the cause, the fix. End with the single highest-leverage change for the next video, and feed the result back into the channel's profile (channel-formula) if one exists.

Common Mistakes

| Mistake | Fix | |---------|-----| | Judging by end-retention or AVD alone | Zone-by-zone against a winner — the cliff decides distribution | | Blaming the script for a 0:30 cliff | Check the click triangle first; the body may be healthy | | Ignoring spikes | Spikes are free R&D — codify what those beats did | | Auditing without a baseline | Same-channel winner first; typical band only as fallback | | One flop = change everything | Change the diagnosed zone only; keep what the graph says worked | | Findings without next-video actions | Every finding ends in a concrete instruction for the next script |

Audit Checklist

  • [ ] Winner baseline (or typical band) overlaid?
  • [ ] 0:30 / 1:00 / 2:00 gaps measured?
  • [ ] Click triangle (thumbnail–title–first frame) checked for mismatch?
  • [ ] Every visible dip mapped to a named script beat?
  • [ ] Premise checked against the channel's winning formula?
  • [ ] Rewatch spikes catalogued?
  • [ ] One highest-leverage fix named for the next video?

Related

  • channel-formula — extracts the winning pattern the flop is checked against; each audit feeds the profile back.
  • long-form-youtube — the structure this audits ("confirm the click", sag-point re-hook).
  • titles-and-thumbnails — fixes for click-triangle mismatches.
  • storytelling-hooks — the levers behind every beat.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.