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 yaxeen/storytelling-skills --skill retention-auditgit clone --depth 1 https://github.com/yaxeen/storytelling-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/yaxeen/storytelling-skills/retention-audit)<a href="https://agentmods.dev/skills/yaxeen/storytelling-skills/retention-audit"><img src="https://agentmods.dev/badge/skills/yaxeen/storytelling-skills/retention-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yaxeen/storytelling-skills/retention-audit"><img src="https://agentmods.dev/badge/skills/yaxeen/storytelling-skills/retention-audit.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00055 | $0.01321 |
| Opus 5 | $0.00028 | $0.00660 |
| Sonnet 5 | $0.00011 | $0.00264 |
| Haiku 4.5 | $0.00006 | $0.00132 |
Grade A, and why
retention-audit 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 12d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 |
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.
- 12d ago First seen · 77 lines · 55 tokens per session scan A a1daf05109fd
retention-audit is a skill published in the GitHub repository yaxeen/storytelling-skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,321 once invoked, about $0.0003 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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