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Agent skill

Memory

by grandamenium in grandamenium/cortextos

You need to write or update memory. An agent skill from grandamenium/cortextos.

MITAuto-check passedAgent Workflows

Install Memory

skills CLI
$ npx skills add grandamenium/cortextos --skill memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install grandamenium/cortextos memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/grandamenium/cortextos.git skills-src && mkdir -p .claude/skills && cp -r skills-src/community/skills/memory .claude/skills/memory && rm -rf skills-src

Use ~/.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/

Facts

Skill name
memory
GitHub stars
101
Token cost
~1.1k tokens
SKILL.md length
263 words
Files
1
Skills in repo
55
Repo updated
First seen
Licence
MIT

At a glance

You need to write or update memory. An agent skill from grandamenium/cortextos.

  • Tasks that involve Context engineering
  • SKILL.md covers Layer 1: Daily Memory…, Layer 2: Long-Term Memory…, Layer 3: Knowledge Base… and Target
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Agent memory

What it does

Memory is an agent skill from grandamenium/cortextos. You need to write or update memory. This happens at session start, heartbeat, session end, or when you learn something worth keeping. Memory is how you maintain continuity across restarts and context compactions — without it, every session starts blind.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Context engineering and Agent memory. The licence is MIT.

When your agent uses it

  • Tasks that involve Context engineering
  • Tasks that involve Agent memory

Example prompts

  • “/memory”

What it can do on your machine

Read from SKILL.md and the folder at commit 6f93838. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Memory loads about 1.1k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 263 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated 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.

SKILL.md

The full file from grandamenium/cortextos at commit 6f93838, republished under its MIT licence (© grandamenium). 263 words, ~1,117 tokens.

Download SKILL.mdSave it as .claude/skills/memory/SKILL.md (or your agent's skills folder).
name
memory
description
You need to write or update memory. This happens at session start, heartbeat, session end, or when you learn something worth keeping. Memory is how you maintain continuity across restarts and context compactions — without it, every session starts blind.
triggers
memory, remember, write memory, update memory, session memory, what was I working on, resume, working on, memory file, daily memory, long-term memory, memory…

Memory

You have three memory layers. All are mandatory. Without memory, session crashes and context compactions leave the next session starting blind.

The purpose of daily memory is not to log activity — it is to capture enough context that you (or a fresh session) can resume intelligently without re-reading everything.

Each entry should answer: "if my context was wiped right now, what would I need to know to resume intelligently?"

Layer 1: Daily Memory (memory/YYYY-MM-DD.md)

Session-scoped context journal. Written at key checkpoints, not continuously.

Location: memory/$(date -u +%Y-%m-%d).md in your agent workspace

On session start
bash
TODAY=$(date -u +%Y-%m-%d)
mkdir -p memory
cat >> "memory/$TODAY.md" << MEMEOF

## Session Start - $(date -u +'%H:%M:%S UTC')
- Status: online
- Crons active: <output of `cortextos bus list-crons $CTX_AGENT_NAME`>
- Inbox: <N messages or "empty">
- Current state: <where things stand — what is in progress, pending, or needs attention>
- Resuming: <what to do next and why, with enough context to act without re-reading everything>
MEMEOF
Mid-work inline note (write immediately when something important happens)
bash
echo "NOTE $(date -u +'%H:%M UTC'): <key decision / discovery / user preference / non-obvious thing>" >> "memory/$TODAY.md"

Don't wait for the heartbeat. Use for: significant decisions, user preferences learned, non-obvious situations, anything you would want the next session to know. One line.

On heartbeat
bash
TODAY=$(date -u +%Y-%m-%d)
cat >> "memory/$TODAY.md" << MEMEOF

## Heartbeat - $(date -u +'%H:%M:%S UTC')
- Current focus: <what I am working on and why>
- Active threads: <anything in progress or being monitored — state of each>
- Key decisions: <decisions made since last entry with brief rationale>
- Context notes: <anything non-obvious — user preferences, environment state, blockers>
- Next: <what I am doing next>
MEMEOF
On session end (before any restart)
bash
TODAY=$(date -u +%Y-%m-%d)
cat >> "memory/$TODAY.md" << MEMEOF

## Session End - $(date -u +'%H:%M:%S UTC')
- Status: [done/interrupted/context-full]
- Current state: [where things stand — specific enough that the next session can resume cold]
- Active threads: [anything in progress or mid-task with current state]
- Key decisions: [significant decisions from this session worth carrying forward]
- For next session: [what to do first and what context is needed]
MEMEOF
Reading today's memory (on resume)
bash
cat "memory/$(date -u +%Y-%m-%d).md" 2>/dev/null || echo "No memory for today yet"

Layer 2: Long-Term Memory (MEMORY.md)

Persistent learnings that survive across all sessions. Not a log — a living document.

Location: MEMORY.md in your agent workspace

When to update
  • Patterns that work or don't work
  • User preferences discovered
  • System behaviors noted
  • Important decisions and their reasons
  • Corrections you received — things you did wrong
  • Anything you'd want to know on the next fresh session
Format
markdown
## [Topic] — YYYY-MM-DD
<what you learned>

Update at every heartbeat and session end. Ingest to KB after updating.

Layer 3: Knowledge Base (RAG/ChromaDB)

Re-ingest MEMORY.md and today's daily memory on every heartbeat so they stay semantically searchable:

bash
cortextos bus kb-ingest ./MEMORY.md ./memory/$(date -u +%Y-%m-%d).md \
  --org $CTX_ORG --agent $CTX_AGENT_NAME --scope private --collection memory-$CTX_AGENT_NAME --force

Target

  • Session start, every heartbeat, session end — minimum 3 entries
  • Each entry captures context state, not just activity
  • Update MEMORY.md at least once per week with durable learnings

© grandamenium, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in community/skills/memory of grandamenium/cortextos.

Open the folder on GitHubat commit 6f93838

Compare with similar skills

Memory 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.

Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Memory this skillgrandamenium/cortextos101—~1.1kAutomated safety check: PassMIT
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: PassApache-2.0
MemPalace Recall for Planningopen-gsd/gsd-core10k1 repos~1.5kAutomated safety check: NotesMIT
Planning with FilesOthmanAdi/planning-with-files27k—~2.9kAutomated safety check: PassMIT
User Thoughts Memorysickn33/agentic-awesome-skills47k1 repos~2.5kAutomated safety check: PassMIT

Similar skills

  • Memori Long-Term Memory

    MemoriLabs/Memori

    Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward.

    17k GitHub stars~2k tokensUpdated 5 days ago
    Agent WorkflowsAuto-check: notes

  • Memori Long-Term Memory

    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.

    17k GitHub stars~2k tokensUpdated 5 days ago
    Agent WorkflowsAuto-check passed

  • MemPalace Recall for Planning

    open-gsd/gsd-core

    Recalls earlier decisions, patterns and surprises from MemPalace memory before planning, behind a config gate that never blocks the planning step.

    10k GitHub starsUsed in 1 repo~1.5k tokens
    Agent WorkflowsAuto-check: notes

  • Planning with Files

    OthmanAdi/planning-with-files

    Keeps a task plan, findings and progress log in markdown files on disk so long agent tasks survive context resets, with Gemini hooks and helper scripts.

    27k GitHub stars~2.9k tokensUpdated 2 days ago
    Agent WorkflowsAuto-check passed

  • User Thoughts Memory

    sickn33/agentic-awesome-skills

    Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.

    47k GitHub starsUsed in 1 repo~2.5k tokens
    Agent WorkflowsAuto-check passed

  • Lemmalog

    JordyZomer/lemmalog

    Externalize working memory and logical state into the lemmalog Datalog engine (MCP).

    329 GitHub stars~2.8k tokensUpdated 7 days ago
    Agent WorkflowsAuto-check passed

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Categories

Questions about Memory

What does Memory do?

You need to write or update memory. An agent skill from grandamenium/cortextos. Memory is an agent skill from grandamenium/cortextos. You need to write or update memory.

When should I use Memory?

Memory fits situations like: tasks that involve Context engineering; tasks that involve Agent memory.

How do I install Memory in Claude Code?

Run `npx skills add grandamenium/cortextos --skill memory -a claude-code`. Or copy the skill folder (community/skills/memory in grandamenium/cortextos) into .claude/skills/memory in your project. Claude Code loads it when a task matches its description.

How do I install Memory in Codex?

Run `npx skills add grandamenium/cortextos --skill memory -a codex`. Or copy the skill folder (community/skills/memory in grandamenium/cortextos) into .agents/skills/memory in your project. Codex loads it when a task matches its description.

Can I use Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add grandamenium/cortextos --skill memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory, .gemini/skills/memory, .github/skills/memory and .opencode/skills/memory in your project.

What does Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Memory is instructions for the agent only.

Does Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Memory use?

Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Memory use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Memory?

Skills that share tags, products or a category with Memory: Memori Long-Term Memory (MemoriLabs/Memori, 17k stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars), MemPalace Recall for Planning (open-gsd/gsd-core, 10k stars) and Planning with Files (OthmanAdi/planning-with-files, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Memory?

grandamenium (a GitHub user) maintains it in grandamenium/cortextos, which has 101 GitHub stars. The repository holds 55 skills in this directory. The repository was last updated on September 23, 2026.

Source: grandamenium/cortextos on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.