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Retention Drop Checker
by
LeroyCreates
· GitHub ↗
· v1.0.1
· MIT-0
231
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install retention-drop-checker
Description
Diagnose why short-video retention drops and suggest practical fixes. Use when views start but audience leaves early.
Usage Guidance
This skill appears coherent and low-risk: it only needs the content you choose to provide (script/transcript, retention curve, or CSV) and will produce diagnostics and optional Python analysis code. Before uploading any retention exports or CSVs, confirm they contain no sensitive or proprietary identifiers (user IDs, PII, or private project data). If the skill returns a Python script, review the code before running it in your environment; run analysis locally or in a trusted environment rather than sending raw analytics to unknown endpoints. Note the license: CC BY-NC-SA for non-commercial use—contact the author for commercial licensing.
Capability Analysis
Type: OpenClaw Skill
Name: retention-drop-checker
Version: 1.0.1
The retention-drop-checker skill is designed to help users analyze audience retention for short-form videos. The instructions in SKILL.md and the output template in references/output-template.md are entirely consistent with the stated purpose of diagnosing video performance. There are no indicators of data exfiltration, malicious execution, or prompt injection attacks.
Capability Assessment
Purpose & Capability
The name and description (diagnosing short-video retention drops and suggesting fixes) match the runtime instructions: ask for retention curves/transcripts, perform qualitative diagnosis, and optionally emit a Python analysis script when structured CSV data is provided. There are no unrelated credential or binary requirements.
Instruction Scope
Instructions stay on-topic (clarify inputs, segment video, diagnose drops, recommend fixes, produce a reusable Python script if the user supplies structured data). One point to note: the skill expects users may upload retention CSVs—while the skill only says to generate analysis code (not to execute or transmit data), uploading analytics can include sensitive or proprietary data; the SKILL.md does not instruct where code should be run or how uploaded data is stored or transmitted.
Install Mechanism
No install spec and no code files beyond SKILL.md and a harmless output template; this is lowest-risk (instruction-only) from an installation perspective.
Credentials
The skill requests no environment variables, credentials, or config paths—there is no disproportionate secret or environment access requested.
Persistence & Privilege
The skill is not always-on, is user-invocable only, and does not request or describe modifying other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install retention-drop-checker - After installation, invoke the skill by name or use
/retention-drop-checker - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Add browser-first guidance or interactive Python workflow improvements
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Retention Drop Checker?
Diagnose why short-video retention drops and suggest practical fixes. Use when views start but audience leaves early. It is an AI Agent Skill for Claude Code / OpenClaw, with 231 downloads so far.
How do I install Retention Drop Checker?
Run "/install retention-drop-checker" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Retention Drop Checker free?
Yes, Retention Drop Checker is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Retention Drop Checker support?
Retention Drop Checker is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Retention Drop Checker?
It is built and maintained by LeroyCreates (@leooooooow); the current version is v1.0.1.
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