Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/yonatangross/orchestkit/remembergit clone --depth 1 https://github.com/yonatangross/orchestkitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.02241 |
| Opus 5 | $0.00031 | $0.01120 |
| Sonnet 5 | $0.00012 | $0.00448 |
| Haiku 4.5 | $0.00006 | $0.00224 |
Grade A, and why
remember scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto-generated from skills/remember/SKILL.md
Source: https://github.com/yonatangross/orchestkit
Remember - Store Decisions and Patterns
Filesystem vs MCP memory (Opus 5 guidance, CC 2.1.111+): Opus 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/*.jsonfiles. Small, structured, session-scoped.- Durable auto-memory (user facts, feedback, project conventions) →
~/.claude/projects/<slug>/memory/*.mdfiles with a one-line index inMEMORY.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
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:
- Knowledge Graph: Entity and relationship storage via
mcp__memory__create_entitiesandmcp__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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 215 lines · 62 tokens per session scan A d2e228086891
remember is a command published in the GitHub repository yonatangross/orchestkit (224 stars, last pushed 2d ago), licensed MIT. It adds 62 tokens to every session and 2,241 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
van
Command "van" from vanzan01/claude-code-sub-agent-collective, covering /van - collective routing engine, 🎯 purpose - smart routing, 🚐 routing flow, 🚀 dual-mode routing protocol and 🧠 immediate agent routing.
mock
Command "mock" from vanzan01/claude-code-sub-agent-collective, covering /mock - mock agent testing command, purpose, mock agent routing, mock chain flow and available mock agents only.
reset-handoff
Reset the agent handoff system by cleaning up state files and logs.
test-handoff-chain
Test the complete handoff automation mechanism using mock agents with real TaskMaster tasks.
autocompact
Save context to file for automated compact workflow.
bug
Reproduce then TDD-fix a ready-for-agent bug ticket in this checkout. Web bugs get a browser repro first.