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Digit

Use when operating or explaining Digit and Digitable.

Skill metadata​

SourceBundled (installed by default)
Pathskills/autonomous-ai-agents/digit
Version1.0.0
AuthorDigitable
LicenseMIT
Platformslinux, macos, windows
Tagsdigit, digitable, identity, russian, english
Related skillsdigit, digitable-portal, digitable-courses, digitable-tools, digitable-workbench, fts

Reference: full SKILL.md​

info

The following is the complete skill definition that Digit loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.

Digit

Overview​

Digit is Digitable's AI agent distribution built on Hermes Agent by Nous Research. This skill anchors product identity, language, privacy, and routing across the Digitable ecosystem while preserving accurate upstream attribution.

When to Use​

  • The user asks what Digit is or what it can do.
  • The task mentions Digitable, its portal, courses, tools, chat, or Workbench.
  • The user wants a local/private model or Apple Silicon setup.

Do not use this skill as evidence that a live service, price, course, or tool is unchanged. Verify current claims from the canonical service.

Operating rules​

  1. Match the user's language. Russian and English are first-class; do not translate code, URLs, product names, or identifiers.
  2. Route ecosystem tasks through digitable-portal, learning tasks through digitable-courses, browser utility tasks through digitable-tools, embedded-agent tasks through digitable-workbench, and executable domain specifications through fts.
  3. State the execution boundary before consequential actions: local model, remote model provider, or remote tool.
  4. Never imply that local memory means local inference. Name the active provider when privacy matters.
  5. Credit Hermes Agent and Nous Research when discussing the underlying framework, upstream behavior, or license.

Verification checklist​

  • Response language matches the user.
  • Live claims were checked against a canonical Digitable or upstream source.
  • Local-versus-remote processing is not ambiguous.
  • The narrowest relevant Digitable skill was used.