cognee-forget
Use when removing data from cognee memory with forget() in the SDK, HTTP API, or CLI — finding which dataset and document hold the content to delete (listing datasets and data items, reading raw content), choosing between deleting one document, a whole dataset, or only the graph/vector memory, and d…
Install / Use
npx skills add topoteretes/cognee --skill cognee-forgetInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of cognee-forget
cognee-forget scores 96/100 on our quality scale, 206th of 2,893 Automation skills we index (top 8%).
Its SKILL.md is 7.5 KB long, well organised into 9 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 30,958 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 13 days ago, so cognee-forget is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
cognee-forget compared with similar skills
All 4 of these similar skills score higher than cognee-forget; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| cognee-forget (this skill)by topoteretes | 96 | 31.0k | 13d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 93.2k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.6k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 86.2k | today | MCP Server |
| crawl4aiby unclecode | 100 | 84.9k | 2d ago | MCP Server |
Frequently asked questions
- How do I install cognee-forget?
- Run
npx skills add topoteretes/cognee --skill cognee-forget. The install tabs above show the steps for each supported agent. - Which AI agents does cognee-forget work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is cognee-forget safe to use?
- It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is cognee-forget still maintained?
- The repository was last updated 13 days ago, so cognee-forget is actively maintained.
Skill content
View source on GitHubname: cognee-forget description: Use when removing data from cognee memory with forget() in the SDK, HTTP API, or CLI — finding which dataset and document hold the content to delete (listing datasets and data items, reading raw content), choosing between deleting one document, a whole dataset, or only the graph/vector memory, and doing it safely.
Remove data with forget()
forget() is cognee's one deletion API. It removes one document, a whole
dataset, or only the derived memory (graph + vectors) while keeping the raw
files. Deletion cannot be undone, so the workflow is always find, read,
confirm, then delete.
Hard limits for agents
- Delete only what the user asked to forget. Identify it by reading the content first; never guess from a file name alone.
- Confirm the exact items with the user before deleting, unless they already named exact ids.
- The widest deletion you may run is
forget(everything=True), and only when the user explicitly asks to wipe all of their memory. Never use any other reset or wipe mechanism to delete data.
Use it
1. Find the dataset
import cognee
datasets = await cognee.datasets.list_datasets() # datasets the user can read
for ds in datasets:
print(ds.id, ds.name)
HTTP: GET /api/v1/datasets. CLI: cognee-cli datasets list.
2. List its documents
items = await cognee.datasets.list_data(dataset_id) # all Data rows, oldest first
for item in items:
print(item.id, item.name, item.extension, item.created_at)
HTTP: GET /api/v1/datasets/{dataset_id}/data?limit=100&offset=0 (limit up
to 1000; GET .../data/count for the total; example:
examples/python/dataset_data_pagination.py). CLI:
cognee-cli datasets data <dataset_uuid>.
Each item has id, name, created_at, extension, mime_type,
raw_data_location, dataset_id, label, external_metadata (including
any node_set), and data_size.
3. Read the content before deciding
Names are often text_<hash>.txt, so read the content to find what the user
means.
- HTTP:
GET /api/v1/datasets/{dataset_id}/data/{data_id}/rawreturns the stored file (404 if it is gone). - SDK: there is no "get raw" helper; open the stored location:
from cognee.infrastructure.files.utils.open_data_file import open_data_file
async with open_data_file(item.raw_data_location, mode="rb") as f:
preview = f.read(2000).decode("utf-8", errors="replace")
Judge matches by meaning, not only by keywords, and show the user the candidates (name + a short preview) before deleting.
4. Delete
| Goal | Call | What remains |
|---|---|---|
| One document | forget(data_id=..., dataset_id=...) (or dataset="name") | Nothing of that document; shared entities stay while another document still references them |
| A whole dataset | forget(dataset="name") or forget(dataset_id=...) | The dataset is deleted outright: the record, its data rows, graph and vector stores, and attributed sessions |
| Rebuild a dataset's graph later | forget(dataset="name", memory_only=True) | Raw files and data rows; graph, vectors, sessions and pipeline status are reset, so the data can be re-processed |
| One document's memory only | forget(dataset="name", data_id=..., memory_only=True) | That document's raw file and row |
| Every dataset the user can delete | forget(everything=True) | Nothing, in any dataset the user has delete on in the current tenant (shared ones included). Only on explicit request (see the hard limits) |
Return values: {"data_id", "dataset_id", "status"} for a document,
{"dataset_id", "status"} for a dataset (plus data_records_reset with
memory_only), {"datasets_removed", "status"} for everything
(datasets_removed counts the datasets the user can read, not the delete
set).
HTTP: POST /api/v1/forget with a JSON body; camelCase and snake_case
keys both work: {"datasetId": "...", "dataId": "..."},
{"dataset": "name", "memoryOnly": true}, {"everything": true}. Invalid
combinations return 422.
CLI: cognee-cli forget --dataset NAME | --dataset-id UUID [--data-id UUID] [--memory-only], or --everything / --all. The CLI
does not ask for confirmation; confirm with the user first.
Pitfalls
- A
data_idthat is not in the dataset returns success and deletes nothing. The delete path treats an unknown id as a custom-graph-model delete. Always take the id fromlist_datafor that same dataset, and check it is still listed afterwards if it matters. - Pass either
datasetordataset_id, not both (ValueError).data_idandmemory_onlyboth need a dataset. memory_onlyis ignored wheneverything=Truein the SDK (the CLI rejects the combination).everything=Truealways deletes everything.- Not found and not allowed look the same. An unknown dataset name and
one the user cannot delete both raise
DatasetNotFoundError. Deleting needs thedeletepermission on the dataset (see thecognee-permissionsskill).everything=Truedeletes every dataset the user hasdeletepermission on in the current tenant, including datasets shared to them with delete rights, not only the ones they own. - Sessions that cited deleted data are invalidated so recall stops returning answers built on it. Agent-trace entries are not invalidated.
- Changing a document is not a delete. To replace a document's content,
use
cognee.update(data_id=..., data=..., dataset_id=...), which keeps its id and re-extracts only the changed parts. cognee.delete()is deprecated; useforget().
How it works
forget() resolves the dataset with the delete permission, then:
- One document →
datasets.delete_data(): takes the dataset lock, deletes the graph nodes and edges the document owns, the matching vectors and edge evidence, invalidates sessions that cited them, then deletes theDatarow. Ownership is tracked per document (source-refs on graph elements), so an entity shared by two documents survives until both are deleted. Raw files are reference-counted by storage location. - A dataset →
datasets.empty_dataset(). memory_only→ drops the dataset's graph/vector memory and resets its pipeline status, leaving raw data for a rebuild.everything→datasets.delete_all()over every dataset the user hasdeleteon in the current tenant, plus a full prune of the session cache (when caching or usage logging is on). This wipes every user's sessions (Redis FLUSHDB / the whole fs cache / all SQL cache tables), not just this user's.
Key files:
cognee/api/v1/forget/forget.py(SDK),routers/get_forget_router.py(HTTP),cognee/cli/commands/forget_command.py(CLI)cognee/api/v1/datasets/datasets.py(list_datasets,list_data,delete_data,empty_dataset,delete_all)cognee/api/v1/datasets/routers/get_datasets_router.py(list, count, raw)cognee/infrastructure/databases/provenance/source_refs.py(per-document ownership of graph elements)cognee/infrastructure/files/utils/open_data_file.py
Extending it
- Anything new that writes graph nodes or edges for a document must record
its source-refs, or
forget(data_id=...)cannot find and remove it. - Anything new that stores per-document data outside the graph (like edge
evidence) needs a cleanup step in the delete path and in
memory_only. - Unit tests for
forget()are incognee/tests/unit/api/v1/forget/(argument validation, the HTTP endpoint,memory_only); cover both the document and thememory_onlypaths for new deletion behaviour.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
