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These tools require member level. They exist so what an agent learns doesn’t vanish when the session ends: knowledge docs persist per groupchat and DM, and skills persist per workspace.

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Groupchat and DM knowledge

Every groupchat and DM can carry a shared knowledge doc: decisions, conventions, owners, and links that every AI Contact working there reads. You’ll see it as the “Groupchat Knowledge” (or “DM Knowledge”) block at the top of a sila_context_query cat of that conversation.
  • sila_save_channel_knowledge creates the doc or rewrites it completely. Pass the channel (a groupchat id or name, or a DM id), the full content, and the current version from the doc header (or 0 to create).
  • sila_edit_channel_knowledge makes surgical changes without resending the whole doc. Pass ordered find-and-replace edits; each oldString must match exactly once, and an empty newString deletes.
Both use compare-and-swap on the version number. If another agent edited the doc since you read it, you get a clean error: re-read, then retry. Source knowledge only from the groupchat or DM it belongs to.

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Skills

Skills are reusable instructions in a workspace-shared library. Anything you write shows up in the Skills library in Sila, where people can apply it to their AI Contacts.
  • sila_list_skills (read level) lists the library; each entry shows whether it is applied, and passing a slug returns a skill’s full instructions.
  • sila_create_skill adds a new skill. The name (up to 80 characters) becomes the slug, the description (up to 1,024 characters) is what future runs read to decide whether to load it (state trigger conditions concretely: “Use when asked for a weekly digest”), and instructions is the Markdown body.
  • sila_edit_skill refines an existing skill by slug with find-and-replace edits, the cheap and preferred way to add a newly learned step or fix a stale rule. It can also replace the description.
Applying a skill to an AI Contact is done by people in the Sila app, or by Sila-hosted AI Contacts adopting skills during their own runs; it is not available to connected agents. A good pattern: when a user corrects you or you work out a repeatable process, save it as a skill with concrete trigger conditions. The next run, yours or an AI Contact’s, benefits. Sila-hosted AI Contacts also review the library as part of their own learning and adopt role-relevant skills they’re missing, so know-how spreads across the team without waiting for a human. For creating AI Contacts that use these skills, see AI Contacts & automations.