memory

name	memory
description	Use when Codex should remember, recall, search, improve, or forget information using Cognee.

Cognee Memory

Use this skill when the user asks Codex to use Cognee as memory, add facts or documents, search a knowledge graph, recall prior context, or improve existing memory.

Rules

• Prefer the server-first paths below (HTTP to the running Cognee server).
• Use uv run cognee-cli ... only when the server is genuinely unreachable.
• Choose a clear dataset name with -d or --dataset-name; ask only if the dataset boundary is genuinely ambiguous.
• Do not ingest secrets, credentials, .env files, private keys, token dumps, or unrelated generated artifacts.
• Before destructive commands such as forget, delete, or --everything, get explicit user confirmation.

Add And Build

Server-first (one-step ingestion):

${CODEX_PLUGIN_ROOT}/scripts/cognee-remember.sh "<text>" --node-set user_context

Use --node-set project_docs for project/code content, --node-set agent_actions for agent notes. The script POSTs directly to /api/v1/remember and returns {"ok": true} on success.

Fallback only — server unreachable:

uv run cognee-cli remember <text-or-path> -d <dataset-name>

For staged work (no HTTP equivalent — CLI only):

uv run cognee-cli add <text-or-path> -d <dataset-name>
uv run cognee-cli cognify -d <dataset-name>

For long processing:

uv run cognee-cli remember <text-or-path> -d <dataset-name> --background
uv run cognee-cli cognify -d <dataset-name> --background

Recall And Search

Server-first (authoritative):

curl -s -X POST "${COGNEE_BASE_URL:-http://localhost:8011}/api/v1/recall" \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: ${COGNEE_API_KEY:-}" \
  -d '{"query": "<question>", "top_k": 10, "only_context": true, "scope": ["graph"]}'

Omit -H "X-Api-Key: ..." for a local single-user server (auth is optional). An empty list [] from the server is authoritative — the server searched and found nothing.

Fallback only — server unreachable:

uv run cognee-cli recall "<question>" -d <dataset-name> -f pretty

Search modes (CLI only):

uv run cognee-cli search "<question>" -d <dataset-name> -t GRAPH_COMPLETION -f pretty
uv run cognee-cli search "<exact passage or citation need>" -d <dataset-name> -t CHUNKS -k 10 -f pretty
uv run cognee-cli search "<code question>" -d <dataset-name> -t CODE -k 10 -f pretty

The server is the source of truth

cognee-cli is a thin client over the running Cognee server and can print empty stdout even when content exists (a serialization quirk). So:

• Never conclude "not found" from an empty/clean CLI run. Confirm against the server directly — this is authoritative.
• Do not re-run the same CLI search to "retry." One server answer is authoritative.
• Omit -d <dataset> to search all your datasets; restricting to one dataset can miss content that lives in another.

Improve Memory

Server-first (session → graph sync):

python3 "${CODEX_PLUGIN_ROOT}/scripts/sync-session-to-graph.py"

Fallback only — server unreachable:

uv run cognee-cli improve -d <dataset-name>

Bridge session feedback or Q&A into the graph:

uv run cognee-cli improve -d <dataset-name> -s <session-id>

For targeted enrichment:

uv run cognee-cli improve -d <dataset-name> --node-name <entity-name>

Forget

Use the narrowest deletion command possible and confirm first:

uv run cognee-cli forget --dataset <dataset-name>
uv run cognee-cli forget --dataset <dataset-name> --data-id <data-uuid>

Avoid uv run cognee-cli forget --everything unless the user explicitly asks to delete all Cognee data.