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Trimmer Js
by
linmillsd7
· GitHub ↗
· v1.0.0
· MIT-0
99
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install trimmer-js
Description
trim video clips into trimmed video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for cutting and trimming...
Usage Guidance
This skill will upload any videos you give it to an external service (mega-api-prod.nemovideo.ai) and will use a NEMO_TOKEN for authorization. The SKILL.md will create an anonymous token for you if one isn't set and may read or write ~/.config/nemovideo/ or check typical install paths to derive a platform header. Before installing or using: (1) confirm the service/domain and owner (there's no homepage and source is unknown); (2) decide whether you are comfortable uploading the specific video content to an external cloud service; (3) ask the publisher where and how tokens are stored (are tokens persisted locally? for how long?); (4) verify privacy/retention and terms for uploaded media; and (5) be cautious about using this with sensitive or private footage. The mismatches between the registry metadata and the SKILL.md (config paths and token-handling behavior) are not definitive proof of maliciousness but are enough to request clarification from the author before trusting the skill.
Capability Analysis
Type: OpenClaw Skill
Name: trimmer-js
Version: 1.0.0
The trimmer-js skill is a well-documented integration for a cloud-based video editing service (nemovideo.ai). It provides the AI agent with specific instructions for managing authentication via anonymous tokens, handling session states, and interacting with a REST API for video processing. The skill's behavior is strictly aligned with its stated purpose of trimming videos, and it includes security-conscious instructions for the agent to avoid exposing tokens or raw API data. No indicators of data exfiltration, malicious execution, or harmful prompt injection were found.
Capability Assessment
Purpose & Capability
The name/description (trim videos via cloud) matches the SKILL.md actions (upload, render, export). Requesting a single service token (NEMO_TOKEN) and calling an external video render API is consistent with the stated purpose. However, the registry metadata reported no required config paths while the SKILL.md frontmatter declares ~/.config/nemovideo/ (incoherence between manifest and runtime instructions).
Instruction Scope
The instructions explicitly tell the agent to POST to https://mega-api-prod.nemovideo.ai, create sessions, upload files (multipart or by URL), stream SSE events, and poll render status. Those operations are expected for a cloud-based trimming service. The instructions also ask the agent to derive headers from the YAML frontmatter and detect install path (~/.clawhub/, ~/.cursor/skills/) which requires inspecting local paths — this is plausible but broader than a purely API-only skill. The SKILL.md also specifies generating an anonymous token if NEMO_TOKEN is absent, which conflicts with declaring NEMO_TOKEN as required (the skill both requires and knows how to obtain the token).
Install Mechanism
No install spec and no code files (instruction-only) — lowest install risk. Nothing is downloaded or written by an installer step in the registry metadata.
Credentials
Only one credential is declared (NEMO_TOKEN), which is appropriate for a single-cloud-backend service. However, SKILL.md instructs the agent to automatically obtain an anonymous token via the API when the env var is missing — that dual behavior (declared required env var but runtime will create one) is inconsistent and worth calling out. The skill's frontmatter also references a config path (~/.config/nemovideo/) that could be used to read or persist credentials; the top-level registry metadata did not list any required config paths, which is a mismatch.
Persistence & Privilege
always:false and no special persistent installation are requested. The skill discusses session tokens and session lifecycle but does not demand always-on or system-wide privileges in the manifest. The potential for the skill to write a token to a config path is implied in the SKILL.md/frontmatter but not explicitly declared as a persistent install action.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install trimmer-js - After installation, invoke the skill by name or use
/trimmer-js - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
trimmer-js 1.0.0 — Initial Release
- Launches Trimmer JS: trims and exports MP4, MOV, AVI, and WebM video clips up to 500MB.
- Cloud GPU processing with automatic session/token setup; handles everything via chat.
- Supports exporting in high-quality 1080p MP4 by default.
- Provides clear instructions for uploads, exports, checking credits, and session management.
- Includes detailed error handling and automatic retry logic for setup and exports.
- Designed for content creators needing fast, precise cloud video trims with no local install required.
Metadata
Frequently Asked Questions
What is Trimmer Js?
trim video clips into trimmed video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for cutting and trimming... It is an AI Agent Skill for Claude Code / OpenClaw, with 99 downloads so far.
How do I install Trimmer Js?
Run "/install trimmer-js" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Trimmer Js free?
Yes, Trimmer Js is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Trimmer Js support?
Trimmer Js is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Trimmer Js?
It is built and maintained by linmillsd7 (@linmillsd7); the current version is v1.0.0.
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