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💻 Development⚙️ Backend🎨 Frontend🚀 DevOps⛓️ Web3 & Blockchain🎭 Creative📄 Documentation📊 Data & AI💼 Business🤖 Automation🔒 Security✦ Other
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  1. Home
  2. ✦Other
  3. ✦Internal Comms
⏱ Pasting from scattered docs→Other — one install

Internal Comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

📦 Other✦Free transformation✦7 languages

WHAT YOU BECOME

Use Cases

Perfect for these scenarios

✦ 01📝

Publish Blog Posts

Create and publish blog posts directly from your app using Write.as API.

✦ 02📰

Automated Newsletters

Generate and distribute newsletters programmatically with minimal effort.

✦ 03📊

Document Management

Store and retrieve documents securely via Write.as's minimalist API.

✦ 04🔗

Content Syndication

Automatically share content across multiple platforms using Write.as.

MEASURED GAIN

Why Choose This Skill

Proven benefits and measurable impact

5x

Faster Publishing

Publish content 5x faster with direct API integration.

50%

Reduced Manual Work

Cut manual content management tasks by 50%.

99.9%

Higher Uptime

Ensure 99.9% uptime for your content delivery.

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 ComposioHQ__awesome-claude-skills/internal-comms/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
ComposioHQ
Category
Other
File size
1.48 KB
Source repository
ComposioHQ__awesome-claude-skills
License
MIT
Metadata
Includes YAML metadata
View GitHub source

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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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Manage Discord channel access — approve pairings, edit allowlists, set DM/group policy. Use when the user asks to pair, approve someone, check who's allowed, or change policy for the Discord channel.

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Adaptyv

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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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