Agent skill

Remember

by yonatangross in yonatangross/orchestkit

Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations.

MITAuto-check: notesKnowledge Management

Install Remember

skills CLI
$ npx skills add yonatangross/orchestkit --skill remember -a claude-code

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

GitHub CLI
$ gh skill install yonatangross/orchestkit remember --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/yonatangross/orchestkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/skills/remember .claude/skills/remember && 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
remember
GitHub stars
288
Token cost
~2.5k tokens
SKILL.md length
754 words
Files
11 (incl. references)
Skills in repo
107
Repo updated
First seen
Licence
MIT

At a glance

Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations.

  • Works in 5 steps: Parse Input → Auto-Detect Category → Extract Lesson (for anti-patterns) → …
  • Something worth persisting across sessions was just learned
  • SKILL.md covers Argument Resolution, Architecture, Usage and Flags, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Remember is an agent skill from yonatangross/orchestkit. Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Use when something worth persisting across sessions was just learned or decided. To search or read existing memory, invoke memory; to debug retrieval internals, memory-fabric; to consolidate, dream.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `references/category-detection.md`, `references/confirmation-templates.md` and `references/entity-extraction-workflow.md`). Compatibility notes: Claude Code 2.1.277+. Requires memory MCP server.

It sits in Knowledge Management, covering Knowledge graphs. It works with Model Context Protocol. The repository describes itself as: The Complete AI Development Toolkit for Claude Code. 106 skills, 36 agents, 171 hooks. Install ork for stable (v9.x), or ork-alpha for the v10 line, which ships daily. The licence is MIT.

When your agent uses it

  • Something worth persisting across sessions was just learned
  • Tasks that involve Knowledge graphs

Example prompts

  • “/remember”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Claude Code 2.1.277+. Requires memory MCP server.
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash, AskUserQuestion, mcp__memory__create_entities, mcp__memory__create_relations, mcp__memory__add_observations, mcp__memory__search_nodes

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Parse Input
  2. Auto-Detect Category
  3. Extract Lesson (for anti-patterns)
  4. Confirm Type + Scope (AskUserQuestion — M118 #1466)
  5. Confirm Storage

What it can do on your machine

Read from SKILL.md and the folder at commit 1f8d8f3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash
    • AskUserQuestion
    • mcp__memory__create_entities
    • mcp__memory__create_relations
    • mcp__memory__add_observations
    • mcp__memory__search_nodes

    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 python).

    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.

  • Compatibility

    Claude Code 2.1.277+. Requires memory MCP server.

    From compatibility in the SKILL.md frontmatter.

Context cost

Remember loads about 2.5k tokens when it runs, and up to ~4.7k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 754 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.7k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, Bash, AskUserQuestion, mcp__memory__create_entities, mcp__memory__create_relations

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 yonatangross/orchestkit at commit 1f8d8f3, republished under its MIT licence (© yonatangross). 754 words, ~2,478 tokens.

Download SKILL.mdSave it as .claude/skills/remember/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
remember
description
Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Use when something worth persisting across sessions was just learned or decided. To search or read existing memory, invoke memory; to debug retrieval internals, memory-fabric; to consolidate, dream.
allowed-tools
Read, Grep, Glob, Bash, AskUserQuestion, mcp__memory__create_entities, mcp__memory__create_relations, mcp__memory__add_observations, mcp__memory__search_nodes
compatibility
Claude Code 2.1.277+. Requires memory MCP server.
license
MIT
argument-hint
[decision-or-pattern]
context
inherit
user-invocable
true
effort
low
model
haiku
metadata.category
workflow-automation
metadata.mcp-server
memory
metadata.version
3.0.1
metadata.author
OrchestKit

Remember - Store Decisions and Patterns

Filesystem vs MCP memory (Opus 5.5 guidance, CC 2.1.111+): Opus 5.5 reads filesystem memory reliably across multi-session work. Use that to your advantage:

  • Short-lived handoff state (current phase, task in-progress, pending approvals) → .claude/chain/*.json files. Small, structured, session-scoped.
  • Durable auto-memory (user facts, feedback, project conventions) → ~/.claude/projects/<slug>/memory/*.md files with a one-line index in MEMORY.md. Read on every session start.
  • Cross-session knowledge graph (typed entities + relations for query traversal) → MCP memory server (this skill's default path). Best when future sessions will search for patterns.

The three are complementary, not alternatives. Prefer fs for anything you'd want to grep; prefer MCP for anything you'd want to traverse.

Store important decisions, patterns, or context in the knowledge graph for future sessions. Supports tracking success/failure outcomes for building a Best Practice Library.

Argument Resolution

python
TEXT = "$ARGUMENTS"        # Full argument string, e.g., "We use cursor pagination"
FLAG = "$ARGUMENTS[0]"     # First token — check for --success, --failed, --category, --agent
# Parse flags from $ARGUMENTS[0], $ARGUMENTS[1] etc. (CC 2.1.59 indexed access)
# Remaining tokens after flags = the text to remember

Architecture

The remember skill uses knowledge graph as storage:

  1. Knowledge Graph: Entity and relationship storage via mcp__memory__create_entities and mcp__memory__create_relations - FREE, zero-config, always works

Benefits:

  • Zero configuration required - works out of the box
  • Explicit relationship queries (e.g., "what does X use?")
  • Cross-referencing between entities
  • No cloud dependency

Automatic Entity Extraction:

  • Extracts capitalized terms as potential entities (PostgreSQL, React, pgvector)
  • Detects agent names (database-engineer, backend-system-architect)
  • Identifies pattern names (cursor-pagination, connection-pooling)
  • Recognizes "X uses Y", "X recommends Y", "X requires Y" relationship patterns

Usage

Store Decisions (Default)
remember <text>
remember --category <category> <text>
remember --success <text>     # Mark as successful pattern
remember --failed <text>      # Mark as anti-pattern
remember --success --category <category> <text>

# Agent-scoped memory
remember --agent <agent-id> <text>         # Store in agent-specific scope
remember --global <text>                   # Store as cross-project best practice

Flags

FlagBehavior
(default)Write to graph
--successMark as successful pattern
--failedMark as anti-pattern
--category <cat>Set category
--agent <agent-id>Scope memory to a specific agent
--globalStore as cross-project best practice

Categories

  • decision - Why we chose X over Y (default)
  • architecture - System design and patterns
  • pattern - Code conventions and standards
  • blocker - Known issues and workarounds
  • constraint - Limitations and requirements
  • preference - User/team preferences
  • pagination - Pagination strategies
  • database - Database patterns
  • authentication - Auth approaches
  • api - API design patterns
  • frontend - Frontend patterns
  • performance - Performance optimizations

Outcome Flags

  • --success - Pattern that worked well (positive outcome)
  • --failed - Pattern that caused problems (anti-pattern)

If neither flag is provided, the memory is stored as neutral (informational).

Workflow

1. Parse Input
Check for --success flag → outcome: success
Check for --failed flag → outcome: failed
Check for --category <category> flag
Check for --agent <agent-id> flag → agent_id: "ork:{agent-id}"
Check for --global flag → use global user_id
Extract the text to remember
If no category specified, auto-detect from content
2. Auto-Detect Category
KeywordsCategory
chose, decided, selecteddecision
architecture, design, systemarchitecture
pattern, convention, stylepattern
blocked, issue, bug, workaroundblocker
must, cannot, required, constraintconstraint
pagination, cursor, offset, pagepagination
database, sql, postgres, querydatabase
auth, jwt, oauth, token, sessionauthentication
api, endpoint, rest, graphqlapi
react, component, frontend, uifrontend
performance, slow, fast, cacheperformance
3. Extract Lesson (for anti-patterns)

If outcome is "failed", look for:

  • "should have", "instead use", "better to"
  • If not found, prompt user: "What should be done instead?"
4-6. Extract Entities and Create Graph

Extract entities (Technology, Agent, Pattern, Project, AntiPattern) from the text, detect relationship patterns ("X uses Y", "chose X over Y", etc.), then create entities and relations in the knowledge graph.

Show full SKILL.md (300 more words)Show less
7. Confirm Type + Scope (AskUserQuestion — M118 #1466)

Auto-classification is best-effort. Before writing, ask the user to confirm both the memory type and the persistence scope. Pre-select the auto-detected type as the default option when the classifier is confident (≥0.9):

python
# Skip when the invocation already specifies type and scope:
#   remember --type=preference --global  → skip, use those values
#   remember --session  → skip, no persistence
#
# Otherwise, ask both:
AskUserQuestion(questions=[
  {"question": "What type of memory?",
   "header": "Type",
   "options": [
     {"label": "Preference", "description": "How I like to work (style, format, tooling)"},
     {"label": "Project fact", "description": "State of THIS codebase (decisions, constraints)"},
     {"label": "Reference", "description": "External system pointer (URL, doc, dashboard)"},
     {"label": "Feedback", "description": "Correction to future behavior — applied as a rule"}
   ]},
  {"question": "Apply to?",
   "header": "Scope",
   "options": [
     {"label": "This project (default)", "description": "Scoped to .claude/projects/<this-project>/memory/"},
     {"label": "All projects (global)", "description": "User-level memory at ~/.claude/memory/"},
     {"label": "This session only", "description": "Print to context but don't persist"}
   ]}
])

Default selection rules:

  • If auto-detected category maps to one of the 4 type options with confidence ≥0.9, that option is pre-selected (the user can still override).
  • "This project" is always the scope default.
  • "This session only" returns immediately without writing — useful when the user wants to surface a fact for the conversation but not commit it.

Global memory writes route to ~/.claude/memory/<filename>.md instead of the project-local memory directory. The MEMORY.md index is updated in whichever scope was selected (project- or user-level).

Load entity extraction rules, type assignment, relationship patterns, and graph creation examples: Read("references/graph-operations.md")

7. Confirm Storage

Display confirmation using the appropriate template (success, anti-pattern, or neutral) showing created entities, relations, and graph stats.

Load output templates and examples: Read("references/confirmation-templates.md")

File-Based Memory Updates

When updating .claude/memory/MEMORY.md or project memory files:

  • PREFER Edit over Write to preserve existing content and avoid overwriting
  • Use stable anchor lines: ## Recent Decisions, ## Patterns, ## Preferences
  • See the memory skill's "Permission-Free File Operations" section for the full Edit pattern
  • This applies to the calling agent's file operations, not to the knowledge graph operations above

References

Load on demand with Read("references/<file>"):

FileContent
category-detection.mdAuto-detection rules for categorizing memories (priority order)
graph-operations.mdEntity extraction, type assignment, relationship patterns, graph creation
confirmation-templates.mdOutput templates (success, anti-pattern, neutral) and usage examples

  • ork:memory - Search, load, sync, visualize (read-side operations)

Error Handling

  • Knowledge graph unavailable → show configuration instructions
  • Empty text → ask user for content; text >2000 chars → truncate with notice
  • Both --success and --failed → ask user to clarify
  • Entity extraction fails → create generic Decision entity; relation fails → create entities first, retry

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

Files

SKILL.md and 10 other files (references) in src/skills/remember of yonatangross/orchestkit.

  • SKILL.md
  • references/category-detection.md
  • references/confirmation-templates.md
  • references/entity-extraction-workflow.md
  • references/examples.md
  • references/graph-operations.md
  • rules/_sections.md
  • rules/duplicate-entity-detection.md
  • rules/entity-relationship-validation.md
  • rules/observation-quality-gate.md
  • test-cases.json

Open the folder on GitHubat commit 1f8d8f3

Compare with similar skills

Remember 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.

Remember compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Remember this skillyonatangross/orchestkit288—~2.5kAutomated safety check: NotesMIT
Gitnexus Guideaws-samples/sample-kolya-br-proxy10610 repos~867Automated safety check: PassMIT-0
Sage Wikixoai/sage-wiki620—~2.4kAutomated safety check: PassMIT
Remnic Entitiesjoshuaswarren/remnic215—~612Automated safety check: PassMIT
Knowledge Layerstudy8677/repobrain1.3k—~324Automated safety check: PassMIT
Memex Best Practicesiamtouchskyer/memex142—~2.9kAutomated safety check: PassMIT

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Questions about Remember

What does Remember do?

Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Remember is an agent skill from yonatangross/orchestkit. Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations.

When should I use Remember?

Remember fits situations like: something worth persisting across sessions was just learned; tasks that involve Knowledge graphs.

How do I install Remember in Claude Code?

Run `npx skills add yonatangross/orchestkit --skill remember -a claude-code`. Or copy the skill folder (src/skills/remember in yonatangross/orchestkit) into .claude/skills/remember in your project. Claude Code loads it when a task matches its description.

How do I install Remember in Codex?

Run `npx skills add yonatangross/orchestkit --skill remember -a codex`. Or copy the skill folder (src/skills/remember in yonatangross/orchestkit) into .agents/skills/remember in your project. Codex loads it when a task matches its description.

Can I use Remember 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 yonatangross/orchestkit --skill remember -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/remember, .gemini/skills/remember, .github/skills/remember and .opencode/skills/remember in your project.

What does Remember need to run?

SKILL.md names no scripts, command-line tools or credentials: Remember is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash, AskUserQuestion, mcp__memory__create_entities, mcp__memory__create_relations, mcp__memory__add_observations, mcp__memory__search_nodes. Compatibility (from SKILL.md): Claude Code 2.1.277+. Requires memory MCP server..

Does Remember 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 Remember safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Remember use?

Remember is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Remember use?

About 2.5k tokens (SKILL.md is roughly 9.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Remember?

Skills that share tags, products or a category with Remember: Gitnexus Guide (aws-samples/sample-kolya-br-proxy, 106 stars), Sage Wiki (xoai/sage-wiki, 620 stars), Remnic Entities (joshuaswarren/remnic, 215 stars) and Knowledge Layer (study8677/repobrain, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Remember?

yonatangross (a GitHub user) maintains it in yonatangross/orchestkit, which has 288 GitHub stars. The repository holds 107 skills in this directory. The repository was last updated on October 6, 2026.

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