create-rule
Create Cursor rules for persistent AI guidance. Use when the user wants to create a rule, add coding standards, set up project…
Use when the user says 'cognee', asks about knowledge graph or graph memory, wants to switch memory backends, or needs a status check, dataset init, or graph view. Covers Cognee endpoints plus the Brain fallback.
Claude Code
$ npx -y skills add coco-research/coco --skill cognee --agent claude-code
Codex
$ npx skills add coco-research/coco --skill cognee -a codex -y
Cursor
$ npx skills add coco-research/coco --skill cognee -a cursor -y
Gemini CLI
$ npx skills add coco-research/coco --skill cognee -a gemini-cli -y
GitHub Copilot
$ npx skills add coco-research/coco --skill cognee -a github-copilot -y
OpenCode
$ npx skills add coco-research/coco --skill cognee -a opencode -y
Windsurf
$ npx skills add coco-research/coco --skill cognee -a windsurf -y
name: cognee description: "Use when the user says 'cognee', asks about knowledge graph or graph memory, wants to switch memory backends, or needs a status check, dataset init, or graph view. Covers Cognee endpoints plus the Brain fallback."
A persistent knowledge graph memory system powered by [Cognee](https://github.com/coco-research/cognee). Stores entities, decisions, events, and relationships as graph nodes with embeddings, enabling semantic search across projects and sessions.
COGNEE="http://localhost:8000" # default; override with COGNEE_BASE_URL
# Status check
curl -s "$COGNEE/health" | jq .
# List datasets
curl -s "$COGNEE/api/v1/datasets" | jq .
# Create a dataset for this project
curl -s -X POST "$COGNEE/api/v1/datasets" \
-H "Content-Type: application/json" \
-d '{"name": "my-project"}' | jq .
# Quick semantic search
curl -s -X POST "$COGNEE/api/v1/search" \
-H "Content-Type: application/json" \
-d '{"query": "what did we decide about authentication", "search_type": "FEELING_LUCKY", "top_k": 10}' | jq .Check if Cognee is reachable and show available datasets.
COGNEE="${COGNEE_BASE_URL:-http://localhost:8000}"
echo "=== Cognee Status ==="
HEALTH=$(curl -s -o /dev/null -w "%{http_code}" "$COGNEE/health" 2>/dev/null)
if [ "$HEALTH" = "200" ]; then
echo "Server: RUNNING at $COGNEE"
echo ""
echo "Datasets:"
curl -s "$COGNEE/api/v1/datasets" | jq -r '.[] | " • \(.name) (\(.id))"'
else
echo "Server: NOT REACHABLE"
echo ""
echo "Start Cognee:"
echo " pip install cognee && cognee server start"
fiCreate a Cognee dataset for the current project.
**Procedure:**
1. Ask the user for the **dataset name** (default: current directory name, slugified). 2. Check if a dataset with that name already exists:
curl -s "$COGNEE/api/v1/datasets" | jq -r '.[].name'
3. If it exists: "Dataset 'X' already exists. Using it." → skip creation. 4. If not: create it:
curl -s -X POST "$COGNEE/api/v1/datasets" \
-H "Content-Type: application/json" \
-d "{\"name\": \"$DATASET_NAME\"}" | jq .5. Confirm:
COGNEE INITIALIZED
==================
Dataset: {name} ({id})
Endpoint: $COGNEE
Next: Use /cognee-store to push knowledge, /cognee-recall to search.Switch which memory backend is primary for this project.
**Options:**
**Behavior:** This sets a preference. Skills that support both backends will check this preference and route accordingly. Default behavior without explicit switch: Brain for local queries, Cognee for cross-project and semantic search.
Show the knowledge graph for a specific entity or the current dataset.
# Get dataset ID first DATASET_ID=$(curl -s "$COGNEE/api/v1/datasets" | jq -r '.[] | select(.name=="my-project") | .id') # View graph curl -s "$COGNEE/api/v1/datasets/$DATASET_ID/graph" | jq .
Cognee and Brain coexist. They are not mutually exclusive:
┌─────────────────────────────────────┐ │ Coco Agent │ ├─────────────────────────────────────┤ │ /cognee-recall │ /brain │ │ /cognee-store │ /brain-update │ ├─────────────────────────────────────┤ │ Cognee (graph) │ Brain (SQLite) │ │ localhost:8000 │ project_brain.db │ └─────────────────────────────────────┘
Before any Cognee operation, check the health endpoint. If unreachable:
Default dataset name = project directory slug. For example:
User can override. Ask once, remember the mapping.
Unlike Brain (one DB per project folder), Cognee datasets are namespaced. An agent working across multiple projects can query multiple datasets in a single search:
curl -s -X POST "$COGNEE/api/v1/search" \
-H "Content-Type: application/json" \
-d '{"query": "authentication decisions", "datasets": ["project-a", "project-b"], "search_type": "FEELING_LUCKY"}' | jq .Cognee must be installed and running:
pip install cognee cognee server start
Verify: `curl http://localhost:8000/health`
495 personas across 13 departments, 229 skills[^installed] and 388 commands in the full catalog (coco 1.9.0, 2026-10-21). Agent skills, slash commands and subagents for Claude Code, Cursor, Codex and other AI coding agents.
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