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cognee-cli

Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.

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Precio sin confirmar★ 30,192 Estrellas de GitHubRegistro actualizado · 27 sept 2026agent-skill

Resumen

Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Use the cognee CLI

cognee-cli ships with the package (entry point in cognee/cli/_cognee.py; each command lives in cognee/cli/commands/). Every command has --help with examples — prefer that over guessing flags. Needs LLM_API_KEY configured, same as the SDK.

Core flow

The memory commands are the primary surface as of cognee 1.x:

cognee-cli remember "Your text here"         # also accepts file paths / URLs
cognee-cli remember ./docs --dataset-name my_project
cognee-cli recall "Your question"            # query the graph
cognee-cli recall "keyword" --query-type CHUNKS
cognee-cli forget --all                      # wipe local state

remember is ingest + graph build in one step (add + cognify under the hood); --background/-b runs the cognify stage in the background, and --dry-run estimates LLM tokens/cost without ingesting. recall takes --datasets/-d, --top-k/-k (default 10), and --session-id/-s.

forget targets --dataset, --dataset-id, --data-id (needs a dataset), or --everything/--all — one unified command covering what delete, prune, and empty_dataset used to do separately.

forget --all does not ask for confirmation. It deletes every dataset immediately, even on a non-interactive stdin. The legacy delete --all prompts Delete ALL data from cognee? [y/N] first, so switching to forget silently drops that safety net — script it with care.

Search types match exactly 7 of the SDK's SearchType enum (cognee/modules/search/types/SearchType.py), those 7 being chosen in (cognee/cli/config.py:SEARCH_TYPE_CHOICES): GRAPH_COMPLETION, RAG_COMPLETION, CHUNKS, SUMMARIES, CODE, CYPHER, GRAPH_REPORT Others must be reached from the SDK, not CLI; e.g. call cognee.recall with query_type=SearchType.TEMPORAL

Note the CLI defaults --query-type to GRAPH_COMPLETION, whereas the SDK's cognee.recall() auto-routes when query_type is omitted.

Session memory and enrichment

Session entries are currently written from the SDK — cognee.remember(..., session_id="chat_1") — not the CLI (cognee-cli remember has no session flag). The CLI side of session memory is reading and bridging:

cognee-cli recall "question" -s chat_1       # session cache first: without -d/-t
                                             # this searches the session directly
cognee-cli sessions get                      # retrieve session Q&A history
cognee-cli improve -d my_project -s chat_1   # bridge session content into the graph
cognee-cli improve -d my_project             # enrich/index the graph (no session)
cognee-cli feedback ...                      # attach feedback to results

improve also takes --node-name, --feedback-alpha (default 0.1), and --background/-b. remember/improve build their graphs through cognify(), so cognify-level settings (e.g. CONTRADICTION_DETECTION=true) apply to them too.

Legacy / lower-level commands

add, cognify, search, memify, and delete still ship and are what the memory commands call underneath. Use them only to drive a single stage in isolation; prefer remember/recall/forget/improve otherwise.

cognee-cli add "text" && cognee-cli cognify  # what `remember` does in one step
cognee-cli search "question"                 # `recall` minus routing/scope/session sources
cognee-cli memify -d my_project              # custom extraction/enrichment tasks
cognee-cli delete --all                      # superseded by `forget --all`

Management

cognee-cli datasets list                     # dataset operations
cognee-cli config get [key] [--show-secrets] # view one/all settings (API keys masked by default)
cognee-cli config set <key> <value>          # set + persist to ./.env in the cwd
cognee-cli config unset <key>                # reset a key to its default (also persisted)
cognee-cli -ui                               # launch API server + UI (see cognee-server skill)
cognee-cli serve --url http://localhost:8000 # connect CLI/SDK to a running instance

Relational DB migrations (Alembic)

cognee-cli upgrade        # apply migrations
cognee-cli downgrade
cognee-cli history
cognee-cli current

Typically needed after version upgrades when the server refuses to start on an old schema.

Gotchas

  • The CLI initializes cognee lazily; the first command in a fresh environment is slow (DB + model setup), later ones are fast.
  • remember (and add) without --dataset-name targets the default dataset main_dataset; recall/search operate across your accessible datasets unless a dataset is given.
  • forget refuses to run bare — pass --dataset, --dataset-id, --data-id (with a dataset), or --everything/--all.
  • Session commands (recall -s, sessions get, improve -s) require CACHING=true (the default) — with it off, session reads return nothing and SDK session writes raise. To cut read latency and token cost while keeping session memory, cognee-cli config set AUTO_FEEDBACK false — by default cognee makes one structured-output LLM call per answered query to self-tune its memory.
  • memify requires one of the arguments -d/--dataset-name --dataset-id
  • config set/config unset write to the .env file in whatever directory you run the command from (creating it if missing). config reset (reset all keys) is still not implemented.
  • Which .env actually wins is not always the cwd one. At import, cognee calls dotenv.load_dotenv(override=True), which resolves relative to the cognee package location, not your working directory. In a source/editable checkout (uv pip install -e .) a .env at the repo root therefore shadows the .env in the directory you ran from — and because override=True, it also beats variables you exported. Symptom: config set appears to do nothing, or the CLI connects to a backend you thought you had overridden. To test against different settings, move the repo .env aside, or set values programmatically after import (cognee.config.set_*). (Under python -c the cwd .env does win, because dotenv falls back to the cwd when __main__ has no __file__ — which is why the same command can behave differently as a script vs. -c.)
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Metadatos del archivo
name: cognee-cli
description: Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.
Ver texto original
---
name: cognee-cli
description: Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.
---

# Use the cognee CLI

`cognee-cli` ships with the package (entry point in `cognee/cli/_cognee.py`;
each command lives in `cognee/cli/commands/`). Every command has
`--help` with examples — prefer that over guessing flags. Needs
`LLM_API_KEY` configured, same as the SDK.

## Core flow

The memory commands are the primary surface as of cognee 1.x:

```bash
cognee-cli remember "Your text here"         # also accepts file paths / URLs
cognee-cli remember ./docs --dataset-name my_project
cognee-cli recall "Your question"            # query the graph
cognee-cli recall "keyword" --query-type CHUNKS
cognee-cli forget --all                      # wipe local state
```

`remember` is ingest + graph build in one step (`add` + `cognify` under the
hood); `--background`/`-b` runs the cognify stage in the background, and
`--dry-run` estimates LLM tokens/cost without ingesting. `recall` takes
`--datasets`/`-d`, `--top-k`/`-k` (default 10), and `--session-id`/`-s`.

`forget` targets `--dataset`, `--dataset-id`, `--data-id` (needs a dataset), or
`--everything`/`--all` — one unified command covering what `delete`, `prune`,
and `empty_dataset` used to do separately.

> **`forget --all` does not ask for confirmation.** It deletes every dataset
> immediately, even on a non-interactive stdin. The legacy `delete --all`
> prompts `Delete ALL data from cognee? [y/N]` first, so switching to `forget`
> silently drops that safety net — script it with care.

Search types match exactly 7 of the SDK's `SearchType` enum (`cognee/modules/search/types/SearchType.py`), those 7 being chosen in (`cognee/cli/config.py:SEARCH_TYPE_CHOICES`):
GRAPH_COMPLETION, RAG_COMPLETION, CHUNKS, SUMMARIES, CODE, CYPHER, GRAPH_REPORT
Others must be reached from the SDK, not CLI; e.g. call cognee.recall with `query_type=SearchType.TEMPORAL`

Note the CLI defaults `--query-type` to `GRAPH_COMPLETION`, whereas the SDK's
`cognee.recall()` auto-routes when `query_type` is omitted.

## Session memory and enrichment

Session entries are currently written from the SDK — `cognee.remember(...,
session_id="chat_1")` — not the CLI (`cognee-cli remember` has no session
flag). The CLI side of session memory is reading and bridging:

```bash
cognee-cli recall "question" -s chat_1       # session cache first: without -d/-t
                                             # this searches the session directly
cognee-cli sessions get                      # retrieve session Q&A history
cognee-cli improve -d my_project -s chat_1   # bridge session content into the graph
cognee-cli improve -d my_project             # enrich/index the graph (no session)
cognee-cli feedback ...                      # attach feedback to results
```

`improve` also takes `--node-name`, `--feedback-alpha` (default 0.1), and
`--background`/`-b`. `remember`/`improve` build their graphs through
`cognify()`, so cognify-level settings (e.g. `CONTRADICTION_DETECTION=true`)
apply to them too.

## Legacy / lower-level commands

`add`, `cognify`, `search`, `memify`, and `delete` still ship and are what the
memory commands call underneath. Use them only to drive a single stage in
isolation; prefer `remember`/`recall`/`forget`/`improve` otherwise.

```bash
cognee-cli add "text" && cognee-cli cognify  # what `remember` does in one step
cognee-cli search "question"                 # `recall` minus routing/scope/session sources
cognee-cli memify -d my_project              # custom extraction/enrichment tasks
cognee-cli delete --all                      # superseded by `forget --all`
```

## Management

```bash
cognee-cli datasets list                     # dataset operations
cognee-cli config get [key] [--show-secrets] # view one/all settings (API keys masked by default)
cognee-cli config set <key> <value>          # set + persist to ./.env in the cwd
cognee-cli config unset <key>                # reset a key to its default (also persisted)
cognee-cli -ui                               # launch API server + UI (see cognee-server skill)
cognee-cli serve --url http://localhost:8000 # connect CLI/SDK to a running instance
```

## Relational DB migrations (Alembic)

```bash
cognee-cli upgrade        # apply migrations
cognee-cli downgrade
cognee-cli history
cognee-cli current
```

Typically needed after version upgrades when the server refuses to start on
an old schema.

## Gotchas

- The CLI initializes cognee lazily; the first command in a fresh environment
  is slow (DB + model setup), later ones are fast.
- `remember` (and `add`) without `--dataset-name` targets the default dataset
  `main_dataset`; `recall`/`search` operate across your accessible datasets
  unless a dataset is given.
- `forget` refuses to run bare — pass `--dataset`, `--dataset-id`, `--data-id`
  (with a dataset), or `--everything`/`--all`.
- Session commands (`recall -s`, `sessions get`, `improve -s`) require
  `CACHING=true` (the default) — with it off, session reads return nothing and
  SDK session writes raise. To cut read latency and token cost while keeping
  session memory, `cognee-cli config set AUTO_FEEDBACK false` — by default
  cognee makes one structured-output LLM call per answered query to self-tune
  its memory.
- `memify` requires one of the arguments -d/--dataset-name --dataset-id
- `config set`/`config unset` write to the `.env` file in whatever directory
  you run the command from (creating it if missing). `config reset` (reset
  *all* keys) is still not implemented.
- **Which `.env` actually wins is not always the cwd one.** At import, cognee
  calls `dotenv.load_dotenv(override=True)`, which resolves relative to the
  *cognee package location*, not your working directory. In a source/editable
  checkout (`uv pip install -e .`) a `.env` at the repo root therefore shadows
  the `.env` in the directory you ran from — and because `override=True`, it
  also beats variables you `export`ed. Symptom: `config set` appears to do
  nothing, or the CLI connects to a backend you thought you had overridden.
  To test against different settings, move the repo `.env` aside, or set
  values programmatically after import (`cognee.config.set_*`). (Under
  `python -c` the cwd `.env` does win, because dotenv falls back to the cwd
  when `__main__` has no `__file__` — which is why the same command can
  behave differently as a script vs. `-c`.)

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Licencia: Apache-2.0

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill documents `forget --all` as a destructive command without confirmation, but it clearly warns users about this risk, so it's acceptable.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Empieza con una tarea pequeña

  1. 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
  2. 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
  3. 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente
topoteretes/cognee
Licencia
Apache-2.0
Versión
1.0.0
Último push de GitHub
23 ago 2026
Registro actualizado
27 sept 2026
Ruta de instrucciones
.claude/skills/cognee-cli/SKILL.md

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

89/100

Excelente

Confianza

64/100

Solo sandbox

Auditoría

80/100

Requiere revisión

Abrir auditoría completaVer informe de evaluación
  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill documents `forget --all` as a destructive command without confirmation, but it clearly warns users about this risk, so it's acceptable.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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      "task": "Use cognee-cli in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/topoteretes-cognee-cli",
    "api": "https://www.openagentskill.com/api/agent/skills/topoteretes-cognee-cli",
    "audit": "https://www.openagentskill.com/skills/topoteretes-cognee-cli/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=topoteretes-cognee-cli&task=Use%20cognee-cli%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20cognee-cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20cognee-cli%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/topoteretes-cognee-cli/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/topoteretes-cognee-cli"
  }
}

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