ai-image-creator
Generate PNG images using AI (multiple models via OpenRouter including Gemini, FLUX.2, Riverflow, SeedDream, GPT-5 Image, proxied through Cloudflare AI Gateway…
Create, move, reorder, or link learning units and documents in the Knowledge base. Use when the user wants to structure content ('create unit Module 3', 'move these docs to lesson 2', 'reorder lessons by logical sequence', 'link doc X to unit Y').
$ npx -y skills add evolution-foundation/evo-nexus --skill knowledge-organize --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/knowledge-organizeContext preview
The summary Claude sees to decide when to auto-load this skill.
Create, move, reorder, or link learning units and documents in the Knowledge base. Use when the user wants to structure content ('create unit Module 3', 'move these docs to lesson 2', 'reorder lessons by logical sequence', 'link doc X to unit Y').
name: knowledge-organize
description: "Create, move, reorder, or link learning units and documents in the Knowledge base. Use when the user wants to structure content ('create unit Module 3', 'move these docs to lesson 2', 'reorder lessons by logical sequence', 'link doc X to unit Y')."Group: **Curation**. Units: create, move, reorder, link documents.
| Name | Type | Required | Description | |---|---|---|---| | `action` | str | yes | `create` \| `move` \| `reorder` \| `link` \| `update` | | `connection` | str | no | Defaults to first ready | | (action-specific args below) | | | |
Args: `space_id` (or `space` slug), `slug`, `title`, `sequence_idx` (optional), `description`, `prerequisites` (list uuids), `metadata` (dict).
from dashboard.backend.sdk_client import evo
unit = evo.post(
"/api/knowledge/v1/units",
{"space_id": space_id, "slug": slug, "title": title, ...},
headers={"X-Knowledge-Connection": connection},
)Args: `document_id`, `unit_id` (null to unlink).
evo.patch(
f"/api/knowledge/v1/documents/{document_id}",
{"unit_id": unit_id},
headers={"X-Knowledge-Connection": connection},
)Args: `space_id`, `ordered_ids` (list of unit uuids in desired order).
evo.post(
"/api/knowledge/v1/units/reorder",
{"space_id": space_id, "ordered_ids": ordered_ids},
headers={"X-Knowledge-Connection": connection},
)Args: `unit_id`, `document_ids` (list).
for doc_id in document_ids:
evo.patch(
f"/api/knowledge/v1/documents/{doc_id}",
{"unit_id": unit_id},
headers={"X-Knowledge-Connection": connection},
)Args: `unit_id`, `title`, `description`, `sequence_idx`, `prerequisites`, `metadata`.
evo.patch(
f"/api/knowledge/v1/units/{unit_id}",
{"title": title, "description": description, ...},
headers={"X-Knowledge-Connection": connection},
)Confirmation per action:
✓ Unit created: {title}
slug: {slug}
space: {space}
sequence_idx: {N}
id: {uuid}For reorder:
✓ Reordered {N} units in space {space}:
1. {title_1}
2. {title_2}
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