datum-dns

Create and troubleshoot Datum Cloud load balancers, hostnames, domains and networks, using the same diagnosis Datum's own assistant runs

22 skills · 1 agent

Deploy containers to Datum Cloud Compute, put them on a public URL, operate them, and find out why a workload isn't running

10 skills

Query audit logs, investigate incidents, and author ActivityPolicies using the Milo Activity service

7 skills · 2 agents

Sign in to Datum Cloud and connect Claude to your projects through the Datum MCP server, with skills for CI service accounts and handing questions to Patch

3 skills · 2 MCP servers · hooks

Query project logs, export metrics to Grafana Cloud, and read the status metrics Datum publishes for your resources

3 skills

ADR lifecycle management — create, index, supersede, and link Architecture Decision Records to code

5 skills · 1 command · 1 agent

Airtable is the database and operations layer for your agents — whether running product, marketing, sales, ops, HR, or a custom business app. It combines structured data with multiplayer visual surfaces (grid, kanban, calendar, gallery, timeline) humans and agents share — plus sync integrations to Jira, Salesforce, Zendesk, Google Drive, Databricks, and the rest of your stack, all backed by enterprise governance. This plugin makes Claude fluent in Airtable: creating bases and schema, working with records, and sharing UI for collaboration. Bundles the official Airtable MCP server.

8 skills · 1 MCP server

Cloud architecture design for AWS/Azure/GCP/OCI, Kubernetes cluster configuration, Terraform infrastructure-as-code, hybrid cloud networking, and multi-cloud cost optimization

8 skills · 7 agents

Prep calls, summarize and follow up, research accounts, review deals and pipeline, and write the forecast, using the CRM, email, calendar and chat tools your team already uses, or uploaded files. Updates records, drafts or sends email, posts to chat and books meetings when you ask.

36 skills · 23 MCP servers

Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.

1 skill · 3 commands · 1 agent

Persistent project planning files with lifecycle hooks that inject selected plan context. Automatic recovery uses project files only. Explicit catchup modes may read same-project local session records to emit aggregate counts or bounded nonce-framed excerpts. Optional gated mode can request continuation on capable hosts and never runs commands declared in Markdown. No network upload path. Installs across 60+ agents.

6 skills · 13 commands · hooks