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💻 Development⚙️ Backend🎨 Frontend🚀 DevOps⛓️ Web3 & Blockchain🎭 Creative📄 Documentation📊 Data & AI💼 Business🤖 Automation🔒 Security✦ Other
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Made with❤for the Claude community

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  1. Home
  2. ✦Other
  3. ✦File Operations
⏱ Pasting from scattered docs→Other — one install

File Operations

Analyze files and get detailed metadata including size, line counts, modification times, and content statistics. Use when users request file information, statistics, or analysis without modifying files.

📦 Other✦Premium script✦7 languages

WHAT YOU BECOME

Use Cases

Perfect for these scenarios

✦ 01🚨

Adverse Event Analysis

Track drug safety reports and identify potential risks or trends in real time

✦ 02🔍

Device Recall Monitoring

Search recall notices for medical devices to ensure compliance and patient safety

✦ 03📋

Regulatory Submission Research

Analyze 510k and PMA submissions for competitor insights and pathway planning

✦ 04💊

Drug Substance Identification

Lookup UNII codes for accurate substance identification and database linking

MEASURED GAIN

Why Choose This Skill

Proven benefits and measurable impact

80%

Faster Safety Research

Reduce time spent gathering FDA safety data from hours to minutes

50x

Regulatory Data Access

Instantly query complex regulatory datasets without manual API integration

100%

Real-Time Monitoring

Eliminate lag between FDA updates and your safety monitoring systems

WHAT YOU GET

What’s Inside

Files, tags and the three-step install

Download or copy the skill file from the source repository.
Put the skill file into Claude's skills directory — ~/.claude/skills/
Restart Claude or run the reload command, and the skill loads automatically.
$ cp mhattingpete__claude-skills-marketplace/code-operations-plugin/skills/file-operations/SKILL.md ~/.claude/skills/

Tip: Read the documentation and the code before first use, so you know what it does and which permissions it needs.

Technical information

Author
mhattingpete
Category
Other
File size
2.48 KB
Source repository
mhattingpete__claude-skills-marketplace
License
MIT
Metadata
Includes YAML metadata
View GitHub source

TAKE IT WITH YOU

$9.9/month
Premium script

Unlock unlimited downloads of all 450+ premium scripts.

All skills come from the open-source community; original authors keep their rights.

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Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

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This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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