Ogham Recall
ogham-mcp/ogham-mcp
Smart retrieval from Ogham shared memory. An agent skill from ogham-mcp/ogham-mcp.
Drives cognee from the terminal with remember, recall, forget and improve memory commands, dataset and config management and database migrations.
$ npx skills add topoteretes/cognee --skill cognee-cli -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install topoteretes/cognee cognee-cli --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/cognee-cli .claude/skills/cognee-cli && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .claude/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cliType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add topoteretes/cognee --skill cognee-cli -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install topoteretes/cognee cognee-cli --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/cognee-cli .agents/skills/cognee-cli && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .agents/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add topoteretes/cognee --skill cognee-cli -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install topoteretes/cognee cognee-cli --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/cognee-cli .cursor/skills/cognee-cli && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .cursor/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/topoteretes/cognee.git --path .agents/skills/cognee-cli--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add topoteretes/cognee --skill cognee-cli -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install topoteretes/cognee cognee-cli --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/cognee-cli .gemini/skills/cognee-cli && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .gemini/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install topoteretes/cognee cognee-cliInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add topoteretes/cognee --skill cognee-cli -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/cognee-cli .github/skills/cognee-cli && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .github/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add topoteretes/cognee --skill cognee-cli -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install topoteretes/cognee cognee-cli --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/topoteretes/cognee.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/cognee-cli .opencode/skills/cognee-cli && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cognee-cli" agent skill from https://github.com/topoteretes/cognee/tree/main/.agents/skills/cognee-cli into .opencode/skills/cognee-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cognee-cli", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
cognee-cliDrives cognee from the terminal with remember, recall, forget and improve memory commands, dataset and config management and database migrations.
The skill covers cognee-cli, which ships with the cognee package and needs LLM_API_KEY configured as the SDK does. The memory commands are the main interface. Remember ingests text, files, folders or URLs and builds the graph in one step, with a dataset name option, a background mode and a --dry-run that estimates LLM token cost. Recall queries the graph with dataset, top-k and session filters, and forget removes data by dataset, dataset ID, data ID or everything.
It warns that forget --all deletes every dataset immediately and does not ask for confirmation, unlike the legacy delete --all, and that --memory-only drops the graph and vectors but keeps the raw files so the data can be rebuilt. Recall accepts 10 of the SDK's 20 search types through --query-type and defaults to HYBRID_COMPLETION, while the rest are SDK-only. Session entries are currently written from the SDK and not the CLI. Migration commands such as upgrade, downgrade and stamp are covered too.
Read from SKILL.md and the folder at commit b57cca1. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
uvpythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
LLM_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Cognee CLI Memory Commands loads about 2.2k tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 766 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
y> <value> # set + persist to ./.env in the cwdconfig set`/`config unset` write to the `.env` file in whatever directory- **Which `.env` actually wins is not always the cwd one.** At import, cogneecheckout (`uv pip install -e .`) a `.env` at the repo root therefore shadowsthe `.env` in the directory you ran from — and because `override=True`, itainst different settings, move the repo `.env` aside, or set`python -c` the cwd `.env` does win, because dotenv falls back to the cwdAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from topoteretes/cognee at commit b57cca1, republished under its Apache-2.0 licence (© topoteretes). 766 words, ~2,204 tokens.
.claude/skills/cognee-cli/SKILL.md (or your agent's skills folder).cognee-cli ships with the package (entry point in cognee/cli/_cognee.py;
each command lives in cognee/cli/commands/). Every command has
--help for its flags, but only a few (demo, memify, eval, serve,
push, upgrade, downgrade, stamp, and search with one CODE example)
include usage examples — for the memory commands use the examples
in this file. Needs LLM_API_KEY configured, same as the SDK.
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 stateremember 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 replacing the older delete and
empty-dataset paths. --memory-only (with a dataset) drops the graph and
vectors but keeps the raw files, so the data can be rebuilt.
forget --alldoes not ask for confirmation. It deletes every dataset immediately, even on a non-interactive stdin. The legacydelete --allpromptsDelete ALL data from cognee? [y/N]first, so switching toforgetsilently drops that safety net — script it with care.
--query-type accepts 10 of the SDK's 20 SearchType values — the list in
cognee/cli/config.py:SEARCH_TYPE_CHOICES: HYBRID_COMPLETION, GRAPH_COMPLETION,
RAG_COMPLETION, CHUNKS, CHUNKS_LEXICAL, SUMMARIES, CODE, CYPHER, GRAPH_REPORT,
SKILLS. The rest (TEMPORAL, TRIPLET_COMPLETION, GRAPH_COMPLETION_COT,
AGENTIC_COMPLETION, NATURAL_LANGUAGE, …) are SDK-only, e.g.
cognee.recall(q, query_type=SearchType.TEMPORAL).
When --query-type is omitted the CLI uses HYBRID_COMPLETION
(DEFAULT_SEARCH_TYPE), whereas the SDK's cognee.recall() auto-routes
between search types. --top-k defaults to 10 on the CLI and 15 in the SDK.
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 resultsimprove also takes --node-name, --feedback-alpha (learning rate in
(0, 1]; default IMPROVE_FEEDBACK_ALPHA, 0.1), --build-global-context-index,
--build-truth-subspace (both opt-in stages; the truth subspace needs
-s), and --background/-b. It prints one line per stage — name, status
(completed / already_completed / skipped / errored) and the skip
reason (e.g. no_session_ids, lock_held, triplet_embedding_disabled).
remember/improve build their graphs through cognify(), so cognify-level
settings (e.g. CONTRADICTION_DETECTION=true) apply to them too.
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`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 instancecognee has two migration chains: the relational schema (Alembic, in
cognee/alembic/) and the graph/vector data chain (slugs registered in
cognee/modules/migrations/registry.py). Both run automatically — at API
server startup and on the first write (remember, add, cognify,
improve, …) in an SDK/CLI process — unless ENABLE_AUTO_MIGRATIONS=false.
So you rarely need these commands; they are for inspecting state, disabled
auto-migration, and rollbacks. There is no migrate command.
cognee-cli current # stamped revision per database (per dataset
# with access control on)
cognee-cli history # the data-migration chain, newest first
cognee-cli upgrade # relational to head, then data chain to head
cognee-cli upgrade <slug> # data chain up to and including <slug>
cognee-cli upgrade --alembic <rev> # pin the relational (Alembic) target
cognee-cli downgrade <slug|base> # REWRITES DATA; revision is required,
# prompts unless --force; --dataset <uuid>
# (repeatable) limits it
cognee-cli stamp <head|base|slug> # set the stored revision WITHOUT running
# anything; prompts unless --force;
# --dataset <uuid> (repeatable) limits itThe positional revision is always a data-chain slug; the relational
target goes through --alembic. downgrade leaves the relational schema
alone unless you pass --alembic. upgrade runs even when
ENABLE_AUTO_MIGRATIONS=false. --alembic-path (or COGNEE_ALEMBIC_PATH)
points at a custom Alembic scripts directory.
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.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-idconfig 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..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.)© topoteretes, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/cognee-cli of topoteretes/cognee.
Open the folder on GitHubat commit b57cca1
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in topoteretes/cognee, which our catalogue first saw on October 7, 2026.
Cognee CLI Memory Commands next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cognee CLI Memory Commands this skilltopoteretes/cognee | 32k | 1 repos | ~2.2k | Automated safety check: Notes | Apache-2.0 | |
| Ogham Recallogham-mcp/ogham-mcp | 115 | — | ~1k | Automated safety check: Pass | MIT | |
| Memori Long-Term MemoryMemoriLabs/Memori | 17k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Using LWC Memory and Graphssickn33/agentic-awesome-skills | 47k | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Ogham Maintainogham-mcp/ogham-mcp | 115 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Memoryautomateyournetwork/netclaw | 675 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 |
ogham-mcp/ogham-mcp
Smart retrieval from Ogham shared memory. An agent skill from ogham-mcp/ogham-mcp.
MemoriLabs/Memori
Adds structured long-term memory to OpenClaw agents, built automatically from sessions, with tools the agent calls to recall facts, summaries and decisions.
sickn33/agentic-awesome-skills
Keeps project decisions, research and verified results available across coding-agent sessions through LWC memory, a document Wiki graph and a CodeGraph code index.
ogham-mcp/ogham-mcp
Admin and maintenance workflows for Ogham shared memory. An agent skill from ogham-mcp/ogham-mcp.
automateyournetwork/netclaw
NetClaw's native persistent memory (spec 033) — structured facts with temporal validity, semantic search across past sessions, decision logging, and entity relationships, backed by SQLite + ChromaDB…
bobmatnyc/claude-mpm
Persistent memory palace system with hierarchical storage (palace/wing/room/closet/drawer), progressive retrieval (L0-L3), and temporal knowledge graph for cross-session context
topoteretes/cognee
Runs the Cognee AI memory platform in Docker, from a one-file prebuilt image to a full compose stack with UI, MCP server, Postgres and Neo4j.
topoteretes/cognee
Installs the cognee AI memory library in a Python environment, sets the LLM key and gets a first remember and recall script running with the Python SDK.
topoteretes/cognee
Guide to using and contributing cognee community packages: database adapters, data-source connectors, custom tasks and retrievers, and Keywords AI observability.
topoteretes/cognee
Defines the shape of cognee's knowledge graph with graph_model: DataPoint node classes, identity and index fields, typed edges and fixes for duplicated nodes.
topoteretes/cognee
Shows how to write custom cognee tasks, chain them into pipelines, store custom DataPoints and run enrichment over the existing graph.
topoteretes/cognee
Removes data from cognee memory with forget(), finding the right dataset and document first and choosing between one document, a dataset or only the graph and vector memory.
Categories
Drives cognee from the terminal with remember, recall, forget and improve memory commands, dataset and config management and database migrations. The skill covers cognee-cli, which ships with the cognee package and needs LLM_API_KEY configured as the SDK does. The memory commands are the main interface.
Cognee CLI Memory Commands fits situations like: storing documents or text in cognee memory from the terminal; querying cognee memory with recall and choosing a search type; removing a dataset or its graph while keeping the raw files; running cognee database migrations.
Run `npx skills add topoteretes/cognee --skill cognee-cli -a claude-code`. Or copy the skill folder (.agents/skills/cognee-cli in topoteretes/cognee) into .claude/skills/cognee-cli in your project. Claude Code loads it when a task matches its description.
Run `npx skills add topoteretes/cognee --skill cognee-cli -a codex`. Or copy the skill folder (.agents/skills/cognee-cli in topoteretes/cognee) into .agents/skills/cognee-cli in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add topoteretes/cognee --skill cognee-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cognee-cli, .gemini/skills/cognee-cli, .github/skills/cognee-cli and .opencode/skills/cognee-cli in your project.
Going by SKILL.md and its folder, Cognee CLI Memory Commands needs the command-line tools its instructions call (uv and python) and credentials named LLM_API_KEY. Our summary lists: cognee installed, with cognee-cli available; LLM_API_KEY configured.
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Cognee CLI Memory Commands is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Cognee CLI Memory Commands: Ogham Recall (ogham-mcp/ogham-mcp, 115 stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars), Using LWC Memory and Graphs (sickn33/agentic-awesome-skills, 47k stars) and Ogham Maintain (ogham-mcp/ogham-mcp, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
topoteretes (a GitHub organization) maintains it in topoteretes/cognee, which has 31,575 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 7, 2026.
Source: topoteretes/cognee on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.